A Brief Survey of Just-In-Time Sequencing for Mixed-Model Systems

Size: px
Start display at page:

Download "A Brief Survey of Just-In-Time Sequencing for Mixed-Model Systems"

Transcription

1 Iteratoa Joura of Operatos Research Iteratoa Joura of Operatos Research Vo., No., (005) A Bref Survey of Just-I-Tme Sequecg for Mxed-Mode Systems Taka Nath hamaa * ad Wesaw Kubak Facuty of Busess Admstrato, Memora Uversty of Newfoudad AB 3X5, St. Joh s, Newfoudad, Caada Abstract The cocept of peazg obs both for beg tardy ad for beg eary has prove oe of most mportat ad ferte research topcs Operatos Research. I ths survey, we cosder ust--tme mxed-mode, mut-eve suppy chas. Obtag a optma sequece a mut-eve cha s a chaegg oear teger programmg probem. Probems for two or more eves are strogy NP-hard. The probem of mmzg devatos betwee actua ad desred producto for sge-eve ca be soved effcety. Aso the mut-eve probems wth peggg assumpto are sovabe by reducg them to the sge-eve. Cycc schedues are optma for sge-eve probem. We preset varous ways of deag wth these probems such as the eegat cocept of baaced words ad dfferet optmzato techques. We provde a short revew of dfferet mathematca modes, dscuss ther compexty ad compare them. The research resuts obtaed past severa years are preseted aog wth ope probems ad possbe extesos. Keywords Noear teger programmg, Schedug theory, Just--tme systems, Baaced (eve) schedues, Baaced words, Computatoa compexty, Poyoma agorthms. INTROUCTION The cetra goa of mxed-mode or fexbe assemby processes s to crease proft by reducg costs. The ust--tme (JIT) producto systems, whch requre producg oy the ecessary product the ecessary quattes at the ecessary tme, have bee used for cotrog such fexbe assemby systems. The teto of these methods s to satsfy the customer demads for a varety of modes wthout hodg arge vetores or currg arge shortages of the products. We assume a fow e maufacturg, caed fexbe trasfer es, where eggbe swtch-over costs from oe mode to aother aow for dversfed sma-ot producto avodg producto of each mode arge-ots. The most mportat optmzato probem that has to be soved for the mxed-modes, ust--tme systems s to determe the sequece whch dfferet modes are produced. Ths souto mpacts the etre suppy cha. There has bee growg terest JIT systems research sce Mode (983), Mteburg (989), cosders the probem of determg the sequece for producg dfferet products o the e that keeps a costat rate of usage of every part used by the e. I other words, the quatty of each part used by the mxed-mode assemby e per ut of tme shoud be kept as costat as possbe. Ths aows very tte varabty the usage of each part from oe tme horzo to the other. Mode (983), states ths as the most mportat goa of a JIT producto system mpemeted by the Toyota compay. Toyota s so-caed Goa Chasg Method, a oca search heurstc, has bee most popuar for sovg the probem. The sequeces referred to as eve, baaced or far sequeces aways keep the actua producto eve ad the desred producto eve as cose to each other as possbe a the tmes. The other producto ssues studed are cyce tmes, ead tmes, work--process ad oadg (Kubak, 993; Mteburg, 989; Mteburg ad Godste, 99; Mode, 983; Okamura ad Yamasha, 979; Kbrdge ad Wester, 963). Mut-eve producto systems, where compoets requred for dfferet modes may or may ot be dstct, make the probem more chaegg tha the sge-eve producto systems where dfferet modes requre the same umber ad mx of compoets. Because of the pu ature of the JIT systems, the producto sequeces at a other ower eves are aso herety fxed as soo as the fa eve producto sequece s fxed. That s why the determato of the sequece of dfferet products at fa assemby eve s cruca. Mteburg (989), provdes a oear teger programmg formuato for the mmzato of tota devato for mxed-mode JIT producto systems uder the assumpto that the products requre approxmatey the same umber ad mx of parts. As optma sequece at the fa assemby eve woud smutaeousy acheve a eve rate of parts usage at the feeder producto eves, ths formuato ca be cosdered as a sge-eve probem. A exact expoeta tme agorthm ad two heurstcs are aso preseted Mteburg (989), Mteburg ad Godste (99), ad Mteburg ad Samo (989), exted the formuato to mut-eve assemby systems. Most of these optmzato probems woud requre eumeratve or expoeta agorthms. Mteburg et a. (990), Yeomas (997), ad Kubak et a. (997), preset dyamc programmg approaches to the mut-eve probems. We refer the reader to Groef et a. (989), Ima ad Buf (99), g ad Cheg (993), Sumchrastet et a. (99), Sumchrast ad Russe (990), Mteburg ad Godste (99), ad Mteburg ad Samo (989) for severa * Correspodg author s e-ma: dhamaa@yahoo.com 83-73X Copyrght 005 ORSTW

2 hamaa ad Kubak: A Bref Survey of Just-I-Tme Sequecg for Mxed-Mode Systems 39 heurstcs for the probem. Kubak ad Seth (99, 994), reduce the mmzato of tota devato JIT probem to a assgmet probem ad thereby preset a effcet optmzato agorthm for ths probem. The agorthm works for more geera sum obectve fuctos cosstg of oegatve covex fuctos of devatos betwee cumuatve average demad ad cumuatve producto of varous modes over tme. Steer ad Yeomas (993), foowg the optmzato agorthm for the tota devato gve Kubak ad Seth (99, 994) gve a graph theoretc optmzato agorthm for mmzg maxmum devato JIT sge-eve sequecg probem. They aso gve a agorthm for mmzg mut-eve maxmum devato JIT assemby systems uder the peggg assumpto (Steer ad Yeomas, 996). If outputs at producto eves whch feed the fa assemby eve are dedcated to the fa product to whch they w be assembed, the the probem wth peggg s equvaet to a weghted sge-eve of probem whch ca the be mmzed by modfed agorthm for u-weghted sge-eve probem. For both maxmum ad tota devatos, there are aways cycc schedues whch are optma, see Steer ad Yeomas (996), ad Kubak (003), whch sgfcaty reduces the computatoa requremets. Brauer ad Crama (004), prove that the mmzato of maxmum devato or botteeck for a sge-eve s Co-NP, but geera, the compexty of the sge eve probems remas ope for the bary ecodg. The mut-eve probem for two or more producto eves s strogy NP-hard, Kubak (993). Brauer ad Crama (004), preset a agebrac approach to the resuts of Steer ad Yeomas (993), ad formuate the sma devato coecture. Kubak (003), presets a geometrc proof of the coecture ad ater Brauer, Jost ad Kubak (004), expot the cocept of baaced words to gve aother proof of the coecture. Kubak (004, 005), presets propertes of JIT sequeces obtaed through mathematcay eegat cocept of baaced words. We refer the terested readers to Vuo (003), for a survey ad the refereces about baaced words. Bautstaet et a. (997), Kubak (993), ad Pa (00), preset effcet agorthms for maxmum devato probem based o the reducto to the botteeck assgmet probem. Bautsta et a. (996) estabsh a terestg k betwee the JIT sequecg ad the apportomet probem. A apportomet probem deas wth the aocato of seats of a egsature amog the states or provces of a ato. Bask ad Shahd (998), cosder the JIT sequecg probem as the quota method of apportomet. Coromas ad Moreo (003), vestgate reatoshps betwee the souto spaces of dfferet obectve fuctos. The pa of the paper s as foows. I Secto, we revew optmzato modes of JIT sequeces. I Sectos 3 ad 4 we survey the effcet agorthms for tota-devato ad maxmum-devato obectve fuctos, respectvey. Secto 5 summarzes the baace propertes of m-max sequeces. The cycc schedues are dscussed Secto 6. Secto 7 reates the optmaty codtos betwee dfferet obectve fuctos. Secto 8 s devoted to the study of computatoa compexty of the probems, heurstc soutos ad a dyamc programmg approach. The fa Secto 9 cudes cocusos wth possbe drectos ad ope questos for further research.. THE MATHEMATICAL PROGRAMMING FORMULATION. Mut-eve formuato A mxed-mode mut-eve suppy cha cossts of a herarchy of severa dstct producto eves (for exampe, products subassembes compoets raw-materas). I these suppy chas, the mutpe copes of dfferet modes are produced at the fa assemby eve. The assemby system aso cotas severa other ower producto eves where subassembes, compoet parts ad raw materas are ether fabrcated or purchased for use the products. Let there be L dfferet producto eves, where,,..., L wth the hghest eve, the product eve. We deote the umber of dfferet part types of eve by ad the demad for part, where,,...,, of eve by d. eotg by t p the umber of tota uts of output at eve requred to produce oe ut of product p, we have d t p d p, the depedet demad for p part of eve determed by the fa product demads d p, p,,...,. Note that t p f p ad 0 otherwse. Let d be the tota output demad d of eve. The demad rato for part of eve s r ad r at each eve,,...,l. Uder the assumpto of o-preemptve schedue, a schedue s competey defed by the sequece of product copes of the product eve. A copy s sad to be stage k, k,,...,, f k uts of product have bee produced at eve. The tota horzo w be of tme uts ad there w be k compete uts of the varous products p at eve durg the frst k stages. ue to the pu ature of the JIT system aog wth the fact that the ower eve outputs are draw as eeded by the fa product eve, the partcuar combato of the products produced at the product eve durg the frst k stages determes the ecessary cumuatve part producto at every other eve. Let x be the ecessary cumuatve producto of k output at eve durg stages through k ad y k x k be the tota output of eve durg stages through k. Ceary, the cumuatve producto of eve

3 hamaa ad Kubak: A Bref Survey of Just-I-Tme Sequecg for Mxed-Mode Systems 40 through the frst k stages s y k x k. The requred cumuatve producto for part at eve, where, through k stages w be xk t p p x pk. Fay, we coud mpose a weght w because of reatve mportace of baacg the schedue for part at eve. The feasbe souto rego s deoted by χ M { XX ( x pk) } where the varabes satsfy the foowg costrats: k p pk,,...,,,...,,,...,, p x t x L k () y x,,..., L, k,..., k k k pk p y x, k,...,, (3) () L QS( ) ( k k ) () k G X x y r Wth ths otato, the mut-eve JIT sequecg probem s equvaet to m{ GX ( ) X χ }, M where G { GAM, GQM, GAS, G QS }. By Kubak et a. (997), w x y r γ p x pk, p k k where γ p w δ p ad δ p t p r t hp. We defe a matrx Γ [ γ ] h p wth L, where γ p represetg the ( + ) m m th row ad pth coum eemet. Let X k ( x,..., ) T k x k be a vector represetg the cumuatve producto at eve through the frst k stages. The pk,,...,, (4) p k x k x x, p,...,, k,...,, (5) pk p( k ) x d, x 0, p,...,, (6) p p p0 x N,,...,,,..., L, k,...,. (7) k I ths paper, N deotes the set of a oegatve tegers. Costrat () esures that the ecessary cumuatve producto of output of eve by the ed of stage k s determed expcty by the quatty of products produced at producto eve. Costrats () ad (3) cacuate the tota cumuatve producto of eve ad, respectvey, through stages to k. Costrat (5) s to esure that the tota producto of every product over k stages s a o-decreasg fucto of k. Costrat (6) guaratees that the producto requremets for each product are met exacty. Costrats (4), (5) ad (7) esure that exacty oe product s schedued for fa assemby durg each stage. The the mxed-mode, mut-eve schedue probem s to seect X ( x pk) that mmzes oe of the foowg m-max/m-sum obectve fucto (s) G ( X) max x y r (8) AM k k k,, QM( ) max( k k ) (9) k,, G X x y r L G ( X) x y r (0) AS k k k GAM( X ) max ΓXk, k where Γ X k max { w xk ykr }. Here, ΓX k, represets the maxmum devato at stage k over a ad. Notce from the matrx represetato that at ay partcuar stage, the devato of ay part of ay eve s determed by the eve sequece. Lkewse, sum devato obectve G ( X ) QS ( X k ) k wth devato matrx Ω Ω[ w δ ] ad the Eucdea orm p m a a of a vector a (a, a,..., a m ). The sequecg probems, maxmum-devato JIT ad tota-devato JIT, are deoted by MJIT ad SJIT probems, respectvey. The probem s oe of the most fudameta probems fexbe ust--tme mxed-mode producto systems, referred to as JIT sequeces. I these formuatos, the m-sum ad m-max obectves are smar to Mteburg ad Samo (989), Steer ad Yeomas (996), ad Kubak et a. (997), respectvey. Note that the m-max obectves seek to mmze the devatos for each output at each stage, whereas the m-sum obectves are cocered for fdg the owest possbe tota devato whch may resut reatvey arge devato for a certa product. The effects of weghts sge-eve as we as other mut-eve probems are cosdered Yeomas (997), Kubak et a. (997), Steer ad Yeomas (996), Mteburg et a. (990), Mteburg ad Godste (99), Mode (983).. Sge-Leve formuato For,...,, gve products (modes), postve

4 hamaa ad Kubak: A Bref Survey of Just-I-Tme Sequecg for Mxed-Mode Systems 4 tegers (demads) d ad covex symmetrc fuctos f of a sge varabe, caed devato, a assumg mmum 0 at 0. The foowg optmzato probems have bee cosdered to mode sge-eve system. Fd a sequece s s s...s wth tota demad d of products,,,...,, where product occurs exacty d tmes that mmzes the foowg obectve fucto (s) F ( s) max f ( x kr ) () M k k, F ( s) f ( x kr ) (3) S k k where x k represets the umber of product occurreces d (copes) the prefx s s...s k, k,...,, ad r,,...,. The foowg two measures of devatos have bee studed the terature. x k kr the absoute - devato obectve, f( xk rk ) ( x k kr ) the squared - devato obectve. The whoe feasbe souto rego x { X X ( x k ) } sge-eve probem s costraed as x k k,...,, k xk, x k, +,...,, k,...,, x, d, x 0 0,...,, x N,...,, k,...,. k, Ths probem s referred to as the Product Rate Varato Probem (PRV) the terature Kubak (993). A souto of ths probem aways keeps the actua producto eve x k ad the desred producto eve r k as cose to each other as possbe a the tmes. A souto s s s...s of the sge-eve MJIT probem for modes s caed B-feasbe (or B-bouded) f max,k f (x k r k ) B hods for the matrx varabes X ( x k ). We deote the sets of a sge-eve B-feasbe soutos by x B. Note that the above formuato gves the foowg umber-theoretc terpretato of JIT sequecg probem: gve ratoa umbers r,,,...,, wth commo deomator, the probem s to fd tegers x k whch optmay approxmate the sequece (kr ) uder the cardaty ad mootocty restrctos defed above (see aso Brauer ad Crama (004) for the refereces). A mut-eve, m-max probem uder the peggg assumpto has bee reduced to a weghted sge-eve probem (Godste ad Mteburg, 988), (see aso Steer ad Yeomas, 996). Smary, the m-sum, mut-eve probem wth peggg ca be reduced to a weghted sge eve probem cosdered by Yeomas (997). Godste ad Mteburg (988), were the frst to provde mathematca formuato of peggg JIT systems (see aso Steer ad Yeomas, 996). Uder the peggg assumpto, parts of output at eve are dedcated to the partcuar product at eve to whch they w be assembed. Ths assumpto decomposes the ower eve parts that w be assembed to dfferet eve products to dsot sets. Wth ths assumpto, the mut-eve AMJIT sequecg probem subect to the costrat set χ wth p,..., M,,...,,,..., L ad k,..., ca be formuated as m max { w x kr, w t x kr }. pk,,, p pk p p pk p Sce t p f p ad 0 otherwse, the above probem s equvaet to m max { x kr } pk,,, L υ max { w t }, υ p pk p, where p p, By droppg the superfuous subscrpt, we obta the foowg weghted sge-eve AMJIT probem m max { υ x kr : X χ}, k, k,,, k,,. (4) 3. EFFICIENTLY SOLVABLE SJIT SEQUENCING I ths secto, we study the sge-eve, m-sum probems wth the obectve defed (3). Uess otherwse specfed, sge eve, m-sum probems w be deoted by SJIT. These resuts are vad for covex, symmetrc, oegatve fuctos whch take vaue 0 at 0. Let Y {(,, k) :,..., ;,..., d ; k,...,}. efe cost C 0 for (,, k) Y wth respect to the dea posto as foows Z r Z ψ < f k Z, k C 0 f k Z, k ψ f >, Z k Z for the -th copy of mode where Z uquey soves f ( kr ) f ( kr ) ad f (x) x, ψ f( r) f( r) f < Z, f( r) f( r) f Z. A subset Y of Y s caed feasbe f t satsfes the

5 hamaa ad Kubak: A Bref Survey of Just-I-Tme Sequecg for Mxed-Mode Systems 4 foowg costrats C. For each k,...,, there s exacty oe (, ),,..., ;,..., d s.t. (,, k) Y,.e., exacty oe copy product at each tme. C. For each (, ),,..., ;,..., d, there s exacty oe k, k,..., s.t. (,, k) Y,.e., each copy s produced exacty oce. C 3. If (,, k), (,, k ) Y ad k < k, the <,.e., ower dces copes are produced earer. Cosder ay set S of trpes (,, k) satsfyg C, C, C 3 ad defe the sequece s s s...s wth s k, f (,, k) S for some,...d correspodg to the set S. The the sequece s s feasbe for ay gve stace (d, d,..., d ) ad foowg resuts hod, Kubak ad Seth (994). Theorem. Let c(s) C (,, k ) for ay S Y. The, a. For ay feasbe S, t hods F ( s) c( S). + f ( ) f k kr b. If S satsfes C adc, the S* satsfyg C, C ad C 3 wth c(s) c(s*) ca be determed O() steps. Moreover, each product copes preserve the order the sequece s*as t does the sequece s. As the term f f( kr ) s k depedet of the set S, that s costat, a optma souto to SJIT woud be a mmedate cosequece f a optma set S s foud. But a optma set caot be obtaed by smpy sovg the Assgmet Probem 5 wth costrats C ad C ad the costs C wth (,, k) S, as the costrat C 3 s ot of the assgmet type. Notce that the atter costrat s esseta as t tes up the copy of a product wth the -th dea posto for the product. The ma dea of the proof s to show that there exsts at east oe optma sequece for the assgmet probem such that copy (, + ) of product shoud appear after the copy (, ). The proof s doe by mathematca ducto. Wth these costs the correspodg assgmet probem has bee formuated as foows, Kubak ad Seth (994): ( d, ) m [ Fs ( ) C x ] (5) (, ) k subect to the costrats k S x, for,..., ;,..., d, ( d, ) x, for k,...,, (, ) where x, f (, ) s assged at posto k, 0, otherwse. Observe that a obvous optma souto coud be obtaed f sequecg a copes ther dea postos were possbe wthout competto for these postos. As ths s ot the case geera, we eed to resove competto to mmze the gve obectve. Ths s doe effcety by sovg the assgmet probem, (Kubak, 993, Kubak ad Seth, 994). Reca that the assgmet probem wth m odes ca be soved O(m 3 ) tme (see Kubak, 993; Kubak ad Seth, 994, for the refereces). The approach proposed by (Kubak ad Seth 99, 994) for the tota devato product rate varato probem s appcabe to ay p orm wth Fs p, ad partcuar to -orm. I the atter case the approach mmzes maxmum devato obectve. Cosequety, souto to mut-eve m-sum probem wth peggg assumpto coud be obtaed as Kubak ad Seth (99). Steer ad Yeomas (994), ook at the m-sum probem as a weghted matchg probem a compete bpartte graph G (V,E), where weghts of the edges equa peaty costs C. The the probem s to fd a perfect matchg wth the mmum sum of the weghts. A compete bpartte graph s defed by troducg the earest ad atest competo tmes possbe for a copy (, ) of product (see Secto 4 for the defto). Moreover, a -bouded souto that s optma (f such souto exsts) coud be obtaed O( og ) tme, sce for B mpes E ( + ). A Pareto optma souto ca be foud O( og ) tme. But the exstece of -bouded soutos optma for m-sum probems s ot aways the case (see Secto 7). The foowg questo remas ope. What s mmum B such that optma souto for m-sum probem s B-bouded? It s kow that a upper boud o the optma m-sum-absoute ad m-sum-squared obectves s though the boud s ot tght (Steer ad Yeomas, 994). For the sake of competeess, we meto that severa heurstcs for sge-eve probem have aready bee vestgated g ad Cheg (993a, 993b), Godste ad Mteburg (988), Ima ad Buf (99), Mteburg ad Godste (99), Mteburg et a. (990), Mteburg ad Samo (989), Sumchrast et a. (99), Sumchrast ad Russe (990). 4. EFFICIENTLY SOLVABLE MJIT SEQUENCING I ths ad Secto 5 we study the m-max probems that are sge-eve wth the obectve defed (). Uess otherwse specfed, sge eve absoute devato m-max probems w be deoted by AMJIT. Steer ad Yeomas (993), study AMJIT probem reducg t to a sge mache schedug decso probem wth reease tmes ad due dates. They represet the probem as a perfect matchg probem a V -covex

6 hamaa ad Kubak: A Bref Survey of Just-I-Tme Sequecg for Mxed-Mode Systems 43 bpartte graph G (V V, E) where the set V {,...,} represets postos ad the set V {(, ),..., ;,..., d } represets the copes of the products. Here, for,..., ad,..., d, the otato (, ) deotes the -th copy of product mode. There exsts a edge {k, (, )} E f ad oy f k es the permssbe terva [E(, ), L(, )] V of reease tme ad due date for the -th copy of the product. They prove the foowg resut (see aso Brauer ad Crama, (004)). Lemma. Let d,..., d be ay stace of AMJIT probem. A sequece s s s...s s B-feasbe f ad oy f for a,..., ad,...d, ths sequece assgs the copy (, ) to the terva [E(, ), L(, )], where B E (, ) r ad + B L (, ) + r deote the reease date ad the due date of the copy (, ) for gve upper boud B. A terestg questo woud be to show smar cosed form formua for other measure of devato, for stace squared devato. Amogst varous versos of the earest due date agorthms for schedug ut tme obs wth reease tmes ad due dates o a sge mache (see Steer ad Yeomas (993) for the refereces), they appy a modfed verso of Gover s (967), O( E ) earest due date (E) agorthm for fdg a maxmum matchg a V -covex bpartte graph G (V V, E) such that each ascedg k V s matched to the umatched copy (, ) wth smaest due date vaue of L(, ) as defed Lemma. They cocude the foowg. Theorem. The AMJIT sequece s s -feasbe f ad oy f the V -covex bpartte graph G wth boud B has a perfect matchg. Moreover, a optma souto ca be determed by a exact pseudo-poyoma agorthm wth compexty O ( og ). Steer ad Yeomas (996), cosder weghted AMJIT probem ad show that a bary search fds a optma souto for the weghted AMJIT O( og (φ G max )) tme, where φ s a postve teger costat depedg upo probem data. The maxmum weght G max max G gves a upper boud ad LB W m G ( r ) gves a ower boud for the optma obectve vaue of the cosdered probem. Theorem 3. A optma souto to the peggg mut-eve AMJIT ca be determed by a exact pseudo-poyoma agorthm O( og (φ G max )) tme. Let B* be the optma vaue of the AMJIT probem. The for ay stace d,,..., of the AMJIT * probem, t hods that B for,..., where, Brauer ad Crama (004). gcd( d, ) A stroger upper boud has bee obtaed by Tdema (980), B. Thus we have ( ) Theorem 4. For ay stace d,,..., ( > ) of the AMJIT probem, the optma vaue B* satsfes the equaty * max, B ( ). As < ( ) whe d for a wth >, ad ( ) most practca cases, both possbtes have to be take to accout. Obvousy, B* 0 for. A stace of the AMJIT sequecg probem s defed as stadard f gcd(d,..., d ). We ca the correspodg sequece stadard. The sma devato coecture states that for 3, a stadard stace (d,..., d ) of the AMJIT probem has B* < / f ad oy f d for,..., Brauer ad Crama (004). Brauer ad Crama (004), prove the coecture for 6 ad coectured t true for a postve. Kubak (003), presets a geometrc proof that the coecture hods true for ay >. Hs proof expots a atura symmetry of reguar poygos scrbed a crce of crcumferece. Subsequety, Brauer, Jost ad Kubak (004), expot the cocept of baaced words to gve aother proof of the coecture (see Secto 5). Thus, we ca state the foowg theorem. Theorem 5. For 3, a stadard stace (d, d,..., d ) of the AMJIT probem has optma vaue B * < / f ad oy f d * for,...,, ad B. Ths resut ca be restated as foows. For gve ratoa umbers r r,..., r wth 3, t hods [ kr ] k for ay teger k f ad oy f r for,...,. The statemet observes that x, kr < / mpes [ kr ] xk, where [x] deotes the roudg of x to the cosest teger. The structure of staces wth B / becomes more compex as x k may the be equa ether to [ kr] kr / or to [ kr] kr +/ for haf-teger kr (Brauer ad Crama, 004). 5. BALANCE WORS AN AMJIT SEQUENCES Brauer ad Crama (004), Brauer, Jost ad Kubak (004), Jost (003), Kubak (003, 005), study the AMJIT sequeces as baaced words. Oe of the ma probems of baaced words practce s to costruct a k

7 hamaa ad Kubak: A Bref Survey of Just-I-Tme Sequecg for Mxed-Mode Systems 44 fte perodc sequece over a fte set of etters where each etter s dstrbuted as evey throughout the sequece as possbe ad each etter occurs wth a gve rate. Ufortuatey, the exstece of baaced sequeces for most rates s ukey. We wrte a fte word as w a a...such that a A { a, a,..., a } for a {,..., }. A factor of egth f 0 of w s word such that f aa+... a+ f. We say that the dex s the posto of the etter a the word w. The rate r of the etter a fte word w s defed as the fracto r w w where w deotes the umber of occurreces of the dex the word w. A fte sequece w w w...for whch u v δ for a wth u v s caed δ-baaced. We deote the fte repetto of a fte word w by w* ww.... A fte word s s caed perodc f s w* for some fte word w. A fte word w s caed symmetrc f w w R where w R s a mrror refecto of w. A fte baaced word s s caed symmetrc ad perodc f s w* for some fte symmetrc word w. Oe way of budg a fte word o fte etter aphabet A usg the umbers ( ) + s r d d descrbed Kubak (005). It buds a fte word as ( ) foows. Labe the pots +, N by the d d ( ) etter, cosder, + N d d ad the correspodg sequece of abes. Break the te by choosg over whe < gvg hgher prorty to a ower dex wheever a cofct eeds to be resoved. Thus a word wth age vector α,,..., d d d ad the startg pot,,..., β, referred d d d to as a hyperboc bard word Vuo (003), s obtaed. Let w be a fte word assocated wth -dmesoa hypercubc bards of age α ad startg pot β. The w s d -baaced o each etter. Moreover, the boud for the baace s aways reached Vuo (003). Jost (003), proves that for ay fte sequece of tota demad d wth maxmum devato B for product rates d, ay fte perodc word w of perod s s -baaced, -baaced or 3-baaced o each product, f B < /, B <3/4ad B <, respectvey. Ay sequece wth d for a,...,, s a -baaced word though ts maxmum devato B > for 3, Kubak (005). However, the maxmum devato B s greater tha 3/4 for the -baaced word a a a a...a a wth d for each,...,. Lkewse, the maxmum devato B s greater tha for the 3-baaced word a a a a a a...a a a wth d 3 for each,..., wth 3. Thus we have Theorem 6. Let s be a fte sequece of egth d / 3/4 wth maxmum devato B for rates r, ad et S, S ad S be the sets of sequeces wth B </, B < 3/4 or B <, / 3/4 respectvey. The S, S ad S are propery cotaed the sets of -baace, -baace ad 3-baace words, respectvey. The resut of Vuo (003) shows that the prorty based cofct resouto apped wheever there s a competto for a dea posto yeds d beg amost the same sze of the aphabet, that s. Theorem 6 shows that the cofct resouto provded by ay agorthm mmzg maxmum devato eads to d beg costat. Thus, t s cear that the cofct resouto provded by ay agorthm mmzg maxmum devato yeds a better baace tha the prorty based cofct resouto apped wheever there s a competto for a dea posto wth mode 3. Theorem 6 combed wth Theorem 4 guaratees the exstece of a optma souto the set of a 3-baaced words. However, t s a ope questo whether there aways exsts a -baaced word that optmzes AMJIT. For 3, the stadard stace satsfes the property of -baaced words Kubak (003), Brauer, Jost ad Kubak (004). Kubak (003), proves that there exsts a perodc, symmetrc ad -baaced word o 3 etters wth destes r r... r, f ad oy f the destes satsfy r (see Theorem 5). It s easy to costruct symmetrc, perodc, -baaced word wth destes gve such a sequece wth 3 etters, oe fxes a ew etter ad serts t betwee every cosecutve etters of s as we as at the begg ad ed of s to obta a sequece for +, etters wth requred propertes. The umber of staces wth -baaced property s fte case of as Brauer ad Crama (004), Kubak (003), prove that the optma vaue of the AMJIT probem s ess tha / f ad oy f oe of the demads s eve ad the other s odd. 6. THE CYCLIC MJIT AN SJIT SEQUENCES I ths secto, we dscuss the exstece of cycc sequece that are optma. As a exstg agorthms have tme compextes depedg o the magtude of the demads d,..., d ad hece o, the exstece of cycc schedue reduces computatoa tme. Therefore, the questo whether the cocateato s m of m copes of a optma sequece s for d, d,..., d s optma for md, md,...,md s mportat for JIT sequecg. Mteburg (989), Mteburg ad Samo (989), observe the exstece of cycc schedues for sum of squared devatos sge-eve. The m-sum probem have such a cycc optma souto f f f for a, where f

8 hamaa ad Kubak: A Bref Survey of Just-I-Tme Sequecg for Mxed-Mode Systems 45 s covex ad symmetrc fucto wth f (0) 0, Bautsta, Compays ad Coromas (997). Kubak ad Kovayov (998), prove that f f (x) f (x) for a wth x (0,) for symmetrc ad covex fucto f, the the cycc schedue for m-sum probem s optma. Moreover, they gve a couterexampe to show that the aswer s egatve f at east oe f s asymmetrc. A the affrmatve aswers have bee based o the foowg two observatos. The frst observato s that f w uv where u ad v are sequeces for the staces βd,..., βd ad γd,..., γd, respectvey, where β, γ are postve tegers, the F S (w) F S (u) + F S (v), Mteburg (989). The secod observato s that eve f oe reaxes the costrats x(w) d,,,...,, the there st exsts a optma sequece w* such that x(w*) d,,,...,, Bautsta, Compays ad Coromas (997). The atter cocuso does ot hod f f are dfferet though covex ad symmetrc f havg the vaues zeros at 0, Kubak ad Kovayov (998). Kubak (003), proves that the set of a optma sequeces for m-sum sge-eve probem cudes cycc sequeces for symmetrc, covex ad oegatve fuctos. I hs proof a dfferet exchage method s used. Theorem 7. Gve d,...,d et s be a optma sequece for the sge-eve m-sum probem SJIT wth covex, symmetrc ad oegatve f,,...,, a assumg mmum 0 at 0. The s m, m, s optma sequece to SJIT for md, md,..., md. A smar resut for sge-eve m-max probem MJIT coud be proved for -orm. Steer ad Yeomas (996), show that the set of optma sequeces for both weghted as we as u-weghted sge-eve m-max probems for absoute devatos cude cycc sequeces. We coecture that cycc JIT sequeces mut-eve probem are optma. 7. RELATIONS BETWEEN IFFERENT OBJECTIVES Coromas ad Moreo (003), prove the foowg. Theorem 8. Let s be ay sequece for sge-eve JIT sequecg probem. The F AS (s) F QS (s) H 0 H(s) where the costat H 0 0 depeds oy o the probem stace, ad H(s) 0 f s s a -bouded souto ad postve otherwse. Furthermore, the m-sum probems for absoute ad squared devatos have the same set of optma soutos o χ, where χ s the set of a -bouded soutos, Coromas ad Moreo (003). Moreover, ay -bouded souto optma for m-sum absoute devato probem (f exsts) s aso optma for m-sum squared devato probem, ad hece, a optma soutos for the atter probem are -bouded Coromas ad Moreo (003). If oe of the m-sum optma souto for squared devato s -bouded, the the probem for absoute devato aso does ot have - bouded souto. A optma souto to the m-sum probem wth absoute devato whch s ot -bouded may ot be optma for the m-sum probem wth squared devato Coromas ad Moreo (003). There may exst a -bouded optma souto to the atter probem eve though oe of the optma souto to the former probem s -bouded. Moreover, ether of these probems may have -bouded optma soutos Coromas ad Moreo (003). Uke the absoute devato ad squared devato obectves for m-sum probems, the sets of -bouded optma soutos wth other covex, symmetrc ad oegatve fuctos are ot the same, Coromas ad Moreo (003). The emprca resuts of Kovayov, Kubak ad Yeomas (00) refute umber of coectures about the reatoshps betwee optma soutos for dfferet obectve fuctos. 8. COMPLEXITY AN YNAMIC PROGRAMMING The questo of the exact compexty of sge-eve JIT sequecg probem remas ope Kubak (993). As the put sze of ay stace (d,, d ) s O( og d ) O ( og ), a agorthm whch s poyoma ad s oy pseudo-poyoma but ot poyoma the put sze. The probem MJIT s Co-NP but t s st ope f the probem s Co-NP-Compete or poyomay sovabe Brauer ad Crama (004). Kubak (993), proves that a verso of mut-eve m-sum probem, referred to as Output Rate Varato Probem, s NP-hard. The mut-eve m-max probem wth absoute devato obectve s strogy NP-hard, Kubak, Steer ad Yeomas (997). However, Kubak, Steer ad Yeomas (997), preset foowg dyamc programmg approach for mut-eve, m-max ad m-sum probems. Let d ( d,..., d ) ( d,..., d ) be the demad vector at eve ad et e be a ut vector of dmeso wth uty the th row. Redefe states a schedue by X ( x,..., x ),where x deotes the cumuatve producto of the product wth x d ad the cardaty of a state X as X x.the mmum vaue of the maxmum devato for a products ad parts over a parta schedues whch ead to state X s defed by ψ (X). The maxmum orm ΓX represets the maxmum devato of actua producto from desred oe over a products ad parts state X at stage k X (see Secto. for the defto of Γ). Foowg dyamc programmg P AM recurso hods for ψ (X) (Yeomas, 997): ψ (Ø) ψ (X : x 0,,,..., ) 0, ψ (X) m{max{ ψ( X e ), Γ X }: x,,,...,

9 hamaa ad Kubak: A Bref Survey of Just-I-Tme Sequecg for Mxed-Mode Systems 46 }. The space ad tme compextes of P AM are O( ( d )) + ad O(m ( d )) +, respectvey. Kubak, Steer ad Yeomas (997), gve extesve expermets to probems of practca sze. They cosder Toyota s schedug appcato descrbed Mode (983), whch requres the producto of 500 products for oe 8-hour producto shft. Two fterg heurstcs were troduced to reduce potetay vast state space to be examed dyamc programmg. They tested four eve radomy geerated probems wth tota product demads 500 ad ut weghts. For a probem wth 6, L 4 ad 400, tme requred to mpemet the agorthm s mutes, for stace. The rato of heurstc souto to the optma souto s.03. Moreover, they cocude that the souto tme of a probem strogy depeds o the umber of dfferet products but oy sghty ot o the rage of part requremets. The dyamc programmg for mut-eve m-max probem s modfed for mut-eve m-sum probem (Yeomas, 997; Kubak et a., 997). The mmum tota squared devato for a products ad parts over a parta schedues of X s defed by φ(x). For the amout of product produced X, et ( Ω X ) deoted by θ (X) be the squared sum of the devatos of actua producto from the desred oe for a products ad parts (see Secto. for the defto of Ω ). The the foowg dyamc programmg P QS recurso hods for φ (X) (Yeomas. 997, Kubak et a 997): φ(ø) φ (X : x 0,,,..., ) 0, { } φ (X) m φ( e ) + θ( ) 9. CONCLUING REMARKS X X : x,,,, }. I ths paper we revewed some research JIT sequecg that has bee carred out t ow. A umber of outstadg ad terestg questos have bee expored whch are st ope ad chaegg. The sge-eve m-sum probems wth ay covex, symmetrc, oegatve fuctos whch take the vaue zero oy at zero devato are sovabe by reducto to the assgmet probem. Ths approach appes to m-max probems as we. A pseudo-poyoma bary search for a feasbe B-bouded sequece obtaed through perfect matchg bpartte graph soves the sge-eve m-max absoute-devato probem. Ths approach ca be apped to other covex, symmetrc, oegatve fuctos. Regardess of the methods, obtag commo soutos to dfferet obectve fuctos woud sgfcaty save the compexty cost. However, the -bouded soutos obtaed va compete bpartte graphs does ot guaratee a optma souto for m-sum probems. The questo, what s mmum B such that optma souto for m-sum probem s B-bouded?, remas ope. Athough most of the sge-eve JIT probems had bee effcety soved by pseudo-poyoma agorthms depedg o the put sze of the demads, ther compexty status s ot yet cear. Eve the basc m-max absoute-devato probem s Co-NP but t s st ope whether the probem s Co-NP-Compete or poyomay sovabe. The mut-eve probems for two or more eves are strogy NP-hard. However, they are effcety sovabe f ether the products requre approxmatey the same umber ad mx of parts or the peggg assumptos are mposed. Therefore, searchg for speca propertes ths cass of probems for whch effcet agorthms exst or ookg for good approxmato agorthms woud be a terestg drecto of research ths area. The exstece of optma schedues that are cycc cosderaby reduces the computatoa requremets for ay type of JIT optmzato probem. Ths probem has bee resoved for sge-eve probems. We coecture that cycc Just--Tme sequeces mut-eve are optma as we. Oe way to dea wth JIT probems s the eegat cocept of baaced words. However, -baaced words caot be obtaed for some rates. The set of a 3-baaced words aways cotas a optma sequece for AMJIT. It s a ope questo whether there aways exsts a -baaced word that s optma for ay gve stace of AMJIT. Characterzatos of baace words to m-max squared-devato ad m-sum probems woud be a terestg probem for further research. ACKNOWLEGEMENT Ths research has bee supported by the Natura Sceces ad Egeerg Couc of Caada research grat OGP REFERENCES. Bask, M. ad Shahd, N. (998). A Smpe Approach to the Product Rate Varato Probem va Axomatcs. Operatos Research Letters, : Bask, M. ad Youg, H.P. (98). Far Represetato: Meetg the Idea of Oe Ma, Oe Vote (Yae Uversty Press, New Have). 3. Bautsta, J., Compays, R., ad Coromas, A. (997a). Modeg ad Sovg the Producto Rate Varato Probem. TOP 5: Bautsta, J., Compays, R., ad Coromas, A. (997b). Resouto of the PRV Probem. Workg Paper.I.T. 97/5, Barceoa. 5. Bautsta, J., Compays, R, ad Coromas, A. (996). A ote o the reato betwee the product rate varato (PRV) ad the apportomet probem. Joura of the Operatos Research

10 hamaa ad Kubak: A Bref Survey of Just-I-Tme Sequecg for Mxed-Mode Systems 47 Socety, 47: Brauer, N. ad Crama, Y. (004). Facts ad questos about the maxmum devato Just--Tme schedug probem. screte Apped Mathematcs, 34: Brauer, N., Jost, V., ad Kubak, W. (004). O Symmetrc Fraeke s ad Sma evatos Coecture. Les cahers du Laboratore Lebz-IMAG, 54, Greobe, Frace. 8. Coromas, A. ad Moreo, N. (003). O the reatos betwee optma soutos for dfferet types of m-sum baaced JIT optmzato probems. INFOR, 4: g, F.Y. ad Cheg, L. (993a). A smpe sequecg agorthm for mxed-mode assemby es Just--Tme producto systems. OR Letters, 3: g, F.Y. ad Cheg, L. (993b). A effectve mxed-mode assemby e sequecg heurstc for Just--Tme producto systems. Joura of Operatos Maagemet, : Gover, F. (967). Maxmum matchg a covex bpartte graph. Nava Research Logstcs Quarterey, 4: Godste, T. ad Mteburg, J. (988). The Effects of Peggg the Schedug of Just--Tme Producto Systems. Workg Paper No. 94, Facuty of Busess, McMaster Uversty, Hamto, Ot. 3. Jost, V. (003). eux probemes d approxmato ophate: Le patage proportoe e ombres etres et Les pavages equbres de Z (EA ROCO, Laboratore Lebz-IMAG). 4. Groef, H. Luss, H., Rosewe, M. ad Wahs, E. (989). Fa assemby sequecg for Just--Tme maufacturg. It. Joura of Producto Research, 7: Ha, R. (983). Zero-Ivetores. ow Joes-Irw, Homewood, IL. 6. Ima, R.R. ad Buf, R.L. (99). Sequecg JIT mxed-mode assemby es. Maagemet Scece, 37: Kbrdge, M.. ad Wester, L. (963). The Le Mode-Mx Sequecg Probem. Proceedgs of the Thrd Iteratoa Coferece o Operatos Research (Oso Egsh Uversty Press). 8. Kovayov, M.Y., Kubak, W. ad Yeomas, J.S. (00). A computatoa study of baaced JIT optmzato agorthms. Iformato Processg ad Operatoa Research, 39: Kubak, W. (005). Baacg Mxed-Mode Suppy Chas, Groupe d tudes et de Recherché e Aayse des ecsos (GERA), Motrea. 0. Kubak, W. (004). Far Sequeces (Hadbook of Schedug, Chapma & Ha/CRC Computer & Iformato Scece Seres).. Kubak, W. (003a). Cycc Just--Tme sequeces are optma. Joura of Goba Optmzato, 7: Kubak, W. (003b). O sma devatos coecture. Buet of the Posh Academy of Sceces, 5: Kubak, W. ad Kovayov, M. (998). Product Rate Varato Probem ad Greatest Commo vsor Property. Workg-Paper: 98-5, Facuty of Busess Admstrato, MUN. 4. Kubak, W., Steer, G., ad Yeomas, J.S. (997). Optma eve schedues for mxed-mode, mut-eve, Just--Tme assemby systems. Aas of Operatos Research, 69: Kubak, W. ad Seth, S.P. (994). Optma Just--Tme schedues for fexbe trasfer es. The Iteratoa Joura of Fexbe Maufacturg Systems, 6: Kubak, W. (993), Mmzg varato of producto rates Just--Tme systems: a survey. Europea Joura of Operatos Research, 66: Kubak, W. ad Seth, S.P. (99). A ote o eve schedues for mxed-mode assemby es ust- tme producto systems, Maagemet Scece, 37: Mteburg, J. ad Godste, T. (99). eveopg producto schedues whch baace part usage ad smooth producto oads for Just--Tme producto systems. Nava Research Logstcs, 38: Mteburg, J., Steer, G. ad Yeomas, S. (990). A dyamc programmg agorthm for schedug mxed-mode, Just--Tme producto systems. Mathematca ad Computer Modeg, 3: Mteburg, J. (989). Leve schedues for mxed-mode assemby es Just--Tme producto systems. Maagemet Scece, 35: Mteburg, J. ad Samo, G. (989). Schedug mxed-mode, muteve assemby es Just--Tme producto systems. Iteratoa Joura of Producto Research, 7: Mode, Y. (983). Toyota Producto Systems (Idustra Egeerg ad Maagemet Press, Norcross, GA). 33. Okamura, K. ad Yamasha, H. (979). A heurstc agorthm for the assemby e mode- mx sequecg probem to mmze the rsk of stoppg the coveyor. Iteratoa J. of Producto Research, 7: Pa, N.M. (00). Sovg the Product Rate Varato Probem (PRVP) of Large mesos as a Assgmet Probem (Ph Thess UPC, Barceoa). 35. Steer, G. ad Yeomas, S. (996). Optma eve schedues mxed-mode mut-eve JIT assemby systems wth peggg. Europea Joura of Operatoa Research, 95: Steer, G. ad Yeomas, S. (994). A bcrtero obectve for eveg the schedue of a mxed-mode, JIT assemby processes, Mathematca & Computer Modeg 0: Steer, G. ad Yeomas, S. (993). Leve schedues for ust tme producto processes, Maagemet Scece 39: St, J.W. (979). A cass of ew methods for cogressoa apportomet, SIAM Joura o Apped Mathematcs 37, Sumchrast, R., Russe, R. ad Tayor, B. (99). A comparatve aayss of sequecg procedures for mxed-mode assemby es Just--Tme producto system. Iteratoa Joura of Producto Research, 30: Sumchrast, R. ad Russe, R. (990). Evauatg mxed-mode assemby e dequecg heurstcs for Just--Tme producto systems. Joura of Operatoa Maagemet, 9: Tdema, R. (980). The charma assgmet probem. screte Mathematcs, 3: Vuo, L. (003). Baaced Words, Rapports de Recherche -006, LIAFA CNRS, Uversté Pars Yeomas, S. (997) Optma Leve Schedues for Mxed-Mode Just--Tme Assemby Systems (Ph.. Thess, McMaster Uversty, Hamto, Otaro).

Lecture 7. Norms and Condition Numbers

Lecture 7. Norms and Condition Numbers Lecture 7 Norms ad Codto Numbers To dscuss the errors umerca probems vovg vectors, t s usefu to empo orms. Vector Norm O a vector space V, a orm s a fucto from V to the set of o-egatve reas that obes three

More information

APPENDIX III THE ENVELOPE PROPERTY

APPENDIX III THE ENVELOPE PROPERTY Apped III APPENDIX III THE ENVELOPE PROPERTY Optmzato mposes a very strog structure o the problem cosdered Ths s the reaso why eoclasscal ecoomcs whch assumes optmzg behavour has bee the most successful

More information

ANOVA Notes Page 1. Analysis of Variance for a One-Way Classification of Data

ANOVA Notes Page 1. Analysis of Variance for a One-Way Classification of Data ANOVA Notes Page Aalss of Varace for a Oe-Wa Classfcato of Data Cosder a sgle factor or treatmet doe at levels (e, there are,, 3, dfferet varatos o the prescrbed treatmet) Wth a gve treatmet level there

More information

A Study of Unrelated Parallel-Machine Scheduling with Deteriorating Maintenance Activities to Minimize the Total Completion Time

A Study of Unrelated Parallel-Machine Scheduling with Deteriorating Maintenance Activities to Minimize the Total Completion Time Joural of Na Ka, Vol. 0, No., pp.5-9 (20) 5 A Study of Urelated Parallel-Mache Schedulg wth Deteroratg Mateace Actvtes to Mze the Total Copleto Te Suh-Jeq Yag, Ja-Yuar Guo, Hs-Tao Lee Departet of Idustral

More information

Application of GA with SVM for Stock Price Prediction in Financial Market

Application of GA with SVM for Stock Price Prediction in Financial Market Iteratoa Joura of Scece ad Research (IJSR) ISSN (Oe): 39-7064 Impact Factor (0): 3.358 Appcato of GA wth SVM for Stock Prce Predcto Faca Market Om Prakash Jea, Dr. Sudarsa Padhy Departmet of Computer Scece

More information

Optimal multi-degree reduction of Bézier curves with constraints of endpoints continuity

Optimal multi-degree reduction of Bézier curves with constraints of endpoints continuity Computer Aded Geometrc Desg 19 (2002 365 377 wwwelsevercom/locate/comad Optmal mult-degree reducto of Bézer curves wth costrats of edpots cotuty Guo-Dog Che, Guo-J Wag State Key Laboratory of CAD&CG, Isttute

More information

Models for Selecting an ERP System with Intuitionistic Trapezoidal Fuzzy Information

Models for Selecting an ERP System with Intuitionistic Trapezoidal Fuzzy Information JOURNAL OF SOFWARE, VOL 5, NO 3, MARCH 00 75 Models for Selectg a ERP System wth Itutostc rapezodal Fuzzy Iformato Guwu We, Ru L Departmet of Ecoomcs ad Maagemet, Chogqg Uversty of Arts ad Sceces, Yogchua,

More information

T = 1/freq, T = 2/freq, T = i/freq, T = n (number of cash flows = freq n) are :

T = 1/freq, T = 2/freq, T = i/freq, T = n (number of cash flows = freq n) are : Bullets bods Let s descrbe frst a fxed rate bod wthout amortzg a more geeral way : Let s ote : C the aual fxed rate t s a percetage N the otoal freq ( 2 4 ) the umber of coupo per year R the redempto of

More information

STOCK INVESTMENT MANAGEMENT UNDER UNCERTAINTY. Madalina Ecaterina ANDREICA 1 Marin ANDREICA 2

STOCK INVESTMENT MANAGEMENT UNDER UNCERTAINTY. Madalina Ecaterina ANDREICA 1 Marin ANDREICA 2 "AROACHES IN ORGANISATIONA MANAGEMENT" 15-16 Noveber 01, BCHAREST, ROMANIA STOCK INVESTMENT MANAGEMENT NDER NCERTAINTY Madaa Ecatera ANDREICA 1 Mar ANDREICA ABSTRACT Ths paper presets a stock vestet aageet

More information

Randomized Load Balancing by Joining and Splitting Bins

Randomized Load Balancing by Joining and Splitting Bins Radomzed Load Baacg by Jog ad Spttg Bs James Aspes Ytog Y 1 Itoducto Cosde the foowg oad baacg sceao: a ceta amout of wo oad s dstbuted amog a set of maches that may chage ove tme as maches o ad eave the

More information

STATISTICAL PROPERTIES OF LEAST SQUARES ESTIMATORS. x, where. = y - ˆ " 1

STATISTICAL PROPERTIES OF LEAST SQUARES ESTIMATORS. x, where. = y - ˆ  1 STATISTICAL PROPERTIES OF LEAST SQUARES ESTIMATORS Recall Assumpto E(Y x) η 0 + η x (lear codtoal mea fucto) Data (x, y ), (x 2, y 2 ),, (x, y ) Least squares estmator ˆ E (Y x) ˆ " 0 + ˆ " x, where ˆ

More information

6.7 Network analysis. 6.7.1 Introduction. References - Network analysis. Topological analysis

6.7 Network analysis. 6.7.1 Introduction. References - Network analysis. Topological analysis 6.7 Network aalyss Le data that explctly store topologcal formato are called etwork data. Besdes spatal operatos, several methods of spatal aalyss are applcable to etwork data. Fgure: Network data Refereces

More information

Abraham Zaks. Technion I.I.T. Haifa ISRAEL. and. University of Haifa, Haifa ISRAEL. Abstract

Abraham Zaks. Technion I.I.T. Haifa ISRAEL. and. University of Haifa, Haifa ISRAEL. Abstract Preset Value of Autes Uder Radom Rates of Iterest By Abraham Zas Techo I.I.T. Hafa ISRAEL ad Uversty of Hafa, Hafa ISRAEL Abstract Some attempts were made to evaluate the future value (FV) of the expected

More information

Online Appendix: Measured Aggregate Gains from International Trade

Online Appendix: Measured Aggregate Gains from International Trade Ole Appedx: Measured Aggregate Gas from Iteratoal Trade Arel Burste UCLA ad NBER Javer Cravo Uversty of Mchga March 3, 2014 I ths ole appedx we derve addtoal results dscussed the paper. I the frst secto,

More information

Integrating Production Scheduling and Maintenance: Practical Implications

Integrating Production Scheduling and Maintenance: Practical Implications Proceedgs of the 2012 Iteratoal Coferece o Idustral Egeerg ad Operatos Maagemet Istabul, Turkey, uly 3 6, 2012 Itegratg Producto Schedulg ad Mateace: Practcal Implcatos Lath A. Hadd ad Umar M. Al-Turk

More information

IDENTIFICATION OF THE DYNAMICS OF THE GOOGLE S RANKING ALGORITHM. A. Khaki Sedigh, Mehdi Roudaki

IDENTIFICATION OF THE DYNAMICS OF THE GOOGLE S RANKING ALGORITHM. A. Khaki Sedigh, Mehdi Roudaki IDENIFICAION OF HE DYNAMICS OF HE GOOGLE S RANKING ALGORIHM A. Khak Sedgh, Mehd Roudak Cotrol Dvso, Departmet of Electrcal Egeerg, K.N.oos Uversty of echology P. O. Box: 16315-1355, ehra, Ira sedgh@eetd.ktu.ac.r,

More information

Finite Difference Method

Finite Difference Method Fte Dfferece Method MEL 87 Computatoa Heat rasfer --4) Dr. Praba audar Assstat Professor Departmet of Mechaca Egeerg II Deh Dscretzato Methods Requred to covert the geera trasport equato to set of agebrac

More information

The simple linear Regression Model

The simple linear Regression Model The smple lear Regresso Model Correlato coeffcet s o-parametrc ad just dcates that two varables are assocated wth oe aother, but t does ot gve a deas of the kd of relatoshp. Regresso models help vestgatg

More information

An SVR-Based Data Farming Technique for Web Application

An SVR-Based Data Farming Technique for Web Application A SVR-Based Data Farmg Techque for Web Appcato Ja L 1 ad Mjg Peg 2 1 Schoo of Ecoomcs ad Maagemet, Behag Uversty 100083 Bejg, P.R. Cha Ja@wyu.c 2 Isttute of Systems Scece ad Techoogy, Wuy Uversty, Jagme

More information

1. The Time Value of Money

1. The Time Value of Money Corporate Face [00-0345]. The Tme Value of Moey. Compoudg ad Dscoutg Captalzato (compoudg, fdg future values) s a process of movg a value forward tme. It yelds the future value gve the relevat compoudg

More information

An Effectiveness of Integrated Portfolio in Bancassurance

An Effectiveness of Integrated Portfolio in Bancassurance A Effectveess of Itegrated Portfolo Bacassurace Taea Karya Research Ceter for Facal Egeerg Isttute of Ecoomc Research Kyoto versty Sayouu Kyoto 606-850 Japa arya@eryoto-uacp Itroducto As s well ow the

More information

10.5 Future Value and Present Value of a General Annuity Due

10.5 Future Value and Present Value of a General Annuity Due Chapter 10 Autes 371 5. Thomas leases a car worth $4,000 at.99% compouded mothly. He agrees to make 36 lease paymets of $330 each at the begg of every moth. What s the buyout prce (resdual value of the

More information

Fractal-Structured Karatsuba`s Algorithm for Binary Field Multiplication: FK

Fractal-Structured Karatsuba`s Algorithm for Binary Field Multiplication: FK Fractal-Structured Karatsuba`s Algorthm for Bary Feld Multplcato: FK *The authors are worg at the Isttute of Mathematcs The Academy of Sceces of DPR Korea. **Address : U Jog dstrct Kwahadog Number Pyogyag

More information

Chapter Eight. f : R R

Chapter Eight. f : R R Chapter Eght f : R R 8. Itroducto We shall ow tur our atteto to the very mportat specal case of fuctos that are real, or scalar, valued. These are sometmes called scalar felds. I the very, but mportat,

More information

How To Make A Supply Chain System Work

How To Make A Supply Chain System Work Iteratoal Joural of Iformato Techology ad Kowledge Maagemet July-December 200, Volume 2, No. 2, pp. 3-35 LATERAL TRANSHIPMENT-A TECHNIQUE FOR INVENTORY CONTROL IN MULTI RETAILER SUPPLY CHAIN SYSTEM Dharamvr

More information

Preprocess a planar map S. Given a query point p, report the face of S containing p. Goal: O(n)-size data structure that enables O(log n) query time.

Preprocess a planar map S. Given a query point p, report the face of S containing p. Goal: O(n)-size data structure that enables O(log n) query time. Computatoal Geometry Chapter 6 Pot Locato 1 Problem Defto Preprocess a plaar map S. Gve a query pot p, report the face of S cotag p. S Goal: O()-sze data structure that eables O(log ) query tme. C p E

More information

of the relationship between time and the value of money.

of the relationship between time and the value of money. TIME AND THE VALUE OF MONEY Most agrbusess maagers are famlar wth the terms compoudg, dscoutg, auty, ad captalzato. That s, most agrbusess maagers have a tutve uderstadg that each term mples some relatoshp

More information

Chapter 3. AMORTIZATION OF LOAN. SINKING FUNDS R =

Chapter 3. AMORTIZATION OF LOAN. SINKING FUNDS R = Chapter 3. AMORTIZATION OF LOAN. SINKING FUNDS Objectves of the Topc: Beg able to formalse ad solve practcal ad mathematcal problems, whch the subjects of loa amortsato ad maagemet of cumulatve fuds are

More information

ECONOMIC CHOICE OF OPTIMUM FEEDER CABLE CONSIDERING RISK ANALYSIS. University of Brasilia (UnB) and The Brazilian Regulatory Agency (ANEEL), Brazil

ECONOMIC CHOICE OF OPTIMUM FEEDER CABLE CONSIDERING RISK ANALYSIS. University of Brasilia (UnB) and The Brazilian Regulatory Agency (ANEEL), Brazil ECONOMIC CHOICE OF OPTIMUM FEEDER CABE CONSIDERING RISK ANAYSIS I Camargo, F Fgueredo, M De Olvera Uversty of Brasla (UB) ad The Brazla Regulatory Agecy (ANEE), Brazl The choce of the approprate cable

More information

Capacitated Production Planning and Inventory Control when Demand is Unpredictable for Most Items: The No B/C Strategy

Capacitated Production Planning and Inventory Control when Demand is Unpredictable for Most Items: The No B/C Strategy SCHOOL OF OPERATIONS RESEARCH AND INDUSTRIAL ENGINEERING COLLEGE OF ENGINEERING CORNELL UNIVERSITY ITHACA, NY 4853-380 TECHNICAL REPORT Jue 200 Capactated Producto Plag ad Ivetory Cotrol whe Demad s Upredctable

More information

Numerical Methods with MS Excel

Numerical Methods with MS Excel TMME, vol4, o.1, p.84 Numercal Methods wth MS Excel M. El-Gebely & B. Yushau 1 Departmet of Mathematcal Sceces Kg Fahd Uversty of Petroleum & Merals. Dhahra, Saud Araba. Abstract: I ths ote we show how

More information

Innovation and Production in the Global Economy Online Appendix

Innovation and Production in the Global Economy Online Appendix Iovato ad Producto te Goba Ecoomy Oe Appedx Costas Aroas Prceto, Yae ad NBER Nataa Ramodo Arzoa State Adrés Rodríguez-Care UC Bereey ad NBER Stepe Yeape Pe State ad NBER December 204 Abstract I ts oe Appedx

More information

SHAPIRO-WILK TEST FOR NORMALITY WITH KNOWN MEAN

SHAPIRO-WILK TEST FOR NORMALITY WITH KNOWN MEAN SHAPIRO-WILK TEST FOR NORMALITY WITH KNOWN MEAN Wojcech Zelńsk Departmet of Ecoometrcs ad Statstcs Warsaw Uversty of Lfe Sceces Nowoursyowska 66, -787 Warszawa e-mal: wojtekzelsk@statystykafo Zofa Hausz,

More information

Chapter 3 0.06 = 3000 ( 1.015 ( 1 ) Present Value of an Annuity. Section 4 Present Value of an Annuity; Amortization

Chapter 3 0.06 = 3000 ( 1.015 ( 1 ) Present Value of an Annuity. Section 4 Present Value of an Annuity; Amortization Chapter 3 Mathematcs of Face Secto 4 Preset Value of a Auty; Amortzato Preset Value of a Auty I ths secto, we wll address the problem of determg the amout that should be deposted to a accout ow at a gve

More information

The Digital Signature Scheme MQQ-SIG

The Digital Signature Scheme MQQ-SIG The Dgtal Sgature Scheme MQQ-SIG Itellectual Property Statemet ad Techcal Descrpto Frst publshed: 10 October 2010, Last update: 20 December 2010 Dalo Glgorosk 1 ad Rue Stesmo Ødegård 2 ad Rue Erled Jese

More information

Approximation Algorithms for Scheduling with Rejection on Two Unrelated Parallel Machines

Approximation Algorithms for Scheduling with Rejection on Two Unrelated Parallel Machines (ICS) Iteratoal oural of dvaced Comuter Scece ad lcatos Vol 6 No 05 romato lgorthms for Schedulg wth eecto o wo Urelated Parallel aches Feg Xahao Zhag Zega Ca College of Scece y Uversty y Shadog Cha 76005

More information

ADAPTATION OF SHAPIRO-WILK TEST TO THE CASE OF KNOWN MEAN

ADAPTATION OF SHAPIRO-WILK TEST TO THE CASE OF KNOWN MEAN Colloquum Bometrcum 4 ADAPTATION OF SHAPIRO-WILK TEST TO THE CASE OF KNOWN MEAN Zofa Hausz, Joaa Tarasńska Departmet of Appled Mathematcs ad Computer Scece Uversty of Lfe Sceces Lubl Akademcka 3, -95 Lubl

More information

CHAPTER 2. Time Value of Money 6-1

CHAPTER 2. Time Value of Money 6-1 CHAPTER 2 Tme Value of Moey 6- Tme Value of Moey (TVM) Tme Les Future value & Preset value Rates of retur Autes & Perpetutes Ueve cash Flow Streams Amortzato 6-2 Tme les 0 2 3 % CF 0 CF CF 2 CF 3 Show

More information

Optimal Packetization Interval for VoIP Applications Over IEEE 802.16 Networks

Optimal Packetization Interval for VoIP Applications Over IEEE 802.16 Networks Optmal Packetzato Iterval for VoIP Applcatos Over IEEE 802.16 Networks Sheha Perera Harsha Srsea Krzysztof Pawlkowsk Departmet of Electrcal & Computer Egeerg Uversty of Caterbury New Zealad sheha@elec.caterbury.ac.z

More information

A Single Machine Scheduling with Periodic Maintenance

A Single Machine Scheduling with Periodic Maintenance A Sgle Mache Schedulg wth Perodc Mateace Fracsco Ágel-Bello Ada Álvarez 2 Joaquí Pacheco 3 Irs Martíez Ceter for Qualty ad Maufacturg, Tecológco de Moterrey, Eugeo Garza Sada 250, 64849 Moterrey, NL, Meco

More information

ON SLANT HELICES AND GENERAL HELICES IN EUCLIDEAN n -SPACE. Yusuf YAYLI 1, Evren ZIPLAR 2. yayli@science.ankara.edu.tr. evrenziplar@yahoo.

ON SLANT HELICES AND GENERAL HELICES IN EUCLIDEAN n -SPACE. Yusuf YAYLI 1, Evren ZIPLAR 2. yayli@science.ankara.edu.tr. evrenziplar@yahoo. ON SLANT HELICES AND ENERAL HELICES IN EUCLIDEAN -SPACE Yusuf YAYLI Evre ZIPLAR Departmet of Mathematcs Faculty of Scece Uversty of Akara Tadoğa Akara Turkey yayl@sceceakaraedutr Departmet of Mathematcs

More information

Simple Linear Regression

Simple Linear Regression Smple Lear Regresso Regresso equato a equato that descrbes the average relatoshp betwee a respose (depedet) ad a eplaator (depedet) varable. 6 8 Slope-tercept equato for a le m b (,6) slope. (,) 6 6 8

More information

Dynamic Two-phase Truncated Rayleigh Model for Release Date Prediction of Software

Dynamic Two-phase Truncated Rayleigh Model for Release Date Prediction of Software J. Software Egeerg & Applcatos 3 63-69 do:.436/jsea..367 Publshed Ole Jue (http://www.scrp.org/joural/jsea) Dyamc Two-phase Trucated Raylegh Model for Release Date Predcto of Software Lafe Qa Qgchua Yao

More information

A particle swarm optimization to vehicle routing problem with fuzzy demands

A particle swarm optimization to vehicle routing problem with fuzzy demands A partcle swarm optmzato to vehcle routg problem wth fuzzy demads Yag Peg, Ye-me Qa A partcle swarm optmzato to vehcle routg problem wth fuzzy demads Yag Peg 1,Ye-me Qa 1 School of computer ad formato

More information

Optimization Model in Human Resource Management for Job Allocation in ICT Project

Optimization Model in Human Resource Management for Job Allocation in ICT Project Optmzato Model Huma Resource Maagemet for Job Allocato ICT Project Optmzato Model Huma Resource Maagemet for Job Allocato ICT Project Saghamtra Mohaty Malaya Kumar Nayak 2 2 Professor ad Head Research

More information

Applications of Support Vector Machine Based on Boolean Kernel to Spam Filtering

Applications of Support Vector Machine Based on Boolean Kernel to Spam Filtering Moder Appled Scece October, 2009 Applcatos of Support Vector Mache Based o Boolea Kerel to Spam Flterg Shugag Lu & Keb Cu School of Computer scece ad techology, North Cha Electrc Power Uversty Hebe 071003,

More information

On Error Detection with Block Codes

On Error Detection with Block Codes BULGARIAN ACADEMY OF SCIENCES CYBERNETICS AND INFORMATION TECHNOLOGIES Volume 9, No 3 Sofa 2009 O Error Detecto wth Block Codes Rostza Doduekova Chalmers Uversty of Techology ad the Uversty of Gotheburg,

More information

Average Price Ratios

Average Price Ratios Average Prce Ratos Morgstar Methodology Paper August 3, 2005 2005 Morgstar, Ic. All rghts reserved. The formato ths documet s the property of Morgstar, Ic. Reproducto or trascrpto by ay meas, whole or

More information

Using Phase Swapping to Solve Load Phase Balancing by ADSCHNN in LV Distribution Network

Using Phase Swapping to Solve Load Phase Balancing by ADSCHNN in LV Distribution Network Iteratoal Joural of Cotrol ad Automato Vol.7, No.7 (204), pp.-4 http://dx.do.org/0.4257/jca.204.7.7.0 Usg Phase Swappg to Solve Load Phase Balacg by ADSCHNN LV Dstrbuto Network Chu-guo Fe ad Ru Wag College

More information

Classic Problems at a Glance using the TVM Solver

Classic Problems at a Glance using the TVM Solver C H A P T E R 2 Classc Problems at a Glace usg the TVM Solver The table below llustrates the most commo types of classc face problems. The formulas are gve for each calculato. A bref troducto to usg the

More information

Proceedings of the 2010 Winter Simulation Conference B. Johansson, S. Jain, J. Montoya-Torres, J. Hugan, and E. Yücesan, eds.

Proceedings of the 2010 Winter Simulation Conference B. Johansson, S. Jain, J. Montoya-Torres, J. Hugan, and E. Yücesan, eds. Proceedgs of the 21 Wter Smulato Coferece B. Johasso, S. Ja, J. Motoya-Torres, J. Huga, ad E. Yücesa, eds. EMPIRICAL METHODS OR TWO-ECHELON INVENTORY MANAGEMENT WITH SERVICE LEVEL CONSTRAINTS BASED ON

More information

AN ALGORITHM ABOUT PARTNER SELECTION PROBLEM ON CLOUD SERVICE PROVIDER BASED ON GENETIC

AN ALGORITHM ABOUT PARTNER SELECTION PROBLEM ON CLOUD SERVICE PROVIDER BASED ON GENETIC Joural of Theoretcal ad Appled Iformato Techology 0 th Aprl 204. Vol. 62 No. 2005-204 JATIT & LLS. All rghts reserved. ISSN: 992-8645 www.jatt.org E-ISSN: 87-395 AN ALGORITHM ABOUT PARTNER SELECTION PROBLEM

More information

An Approach to Evaluating the Computer Network Security with Hesitant Fuzzy Information

An Approach to Evaluating the Computer Network Security with Hesitant Fuzzy Information A Approach to Evaluatg the Computer Network Securty wth Hestat Fuzzy Iformato Jafeg Dog A Approach to Evaluatg the Computer Network Securty wth Hestat Fuzzy Iformato Jafeg Dog, Frst ad Correspodg Author

More information

Based on PSO cloud computing server points location searching

Based on PSO cloud computing server points location searching Iteratoa Worshop o Coud Coput ad Iforato Securty (CCIS 13) Based o PSO coud coput server pots ocato search Che Hua-sha Iforato Techooy Ceter Shaha Iteratoa Studes Uversty Shaha, cha, 1391641563 E-a: huasha@shsu.edu.c

More information

The Gompertz-Makeham distribution. Fredrik Norström. Supervisor: Yuri Belyaev

The Gompertz-Makeham distribution. Fredrik Norström. Supervisor: Yuri Belyaev The Gompertz-Makeham dstrbuto by Fredrk Norström Master s thess Mathematcal Statstcs, Umeå Uversty, 997 Supervsor: Yur Belyaev Abstract Ths work s about the Gompertz-Makeham dstrbuto. The dstrbuto has

More information

The analysis of annuities relies on the formula for geometric sums: r k = rn+1 1 r 1. (2.1) k=0

The analysis of annuities relies on the formula for geometric sums: r k = rn+1 1 r 1. (2.1) k=0 Chapter 2 Autes ad loas A auty s a sequece of paymets wth fxed frequecy. The term auty orgally referred to aual paymets (hece the ame), but t s ow also used for paymets wth ay frequecy. Autes appear may

More information

Statistical Decision Theory: Concepts, Methods and Applications. (Special topics in Probabilistic Graphical Models)

Statistical Decision Theory: Concepts, Methods and Applications. (Special topics in Probabilistic Graphical Models) Statstcal Decso Theory: Cocepts, Methods ad Applcatos (Specal topcs Probablstc Graphcal Models) FIRST COMPLETE DRAFT November 30, 003 Supervsor: Professor J. Rosethal STA4000Y Aal Mazumder 9506380 Part

More information

On Application-level Load Balancing in FastReplica

On Application-level Load Balancing in FastReplica O Appcato-eve Load Baacg FastRepca Jagwo Lee, Gustavo de Vecaa Abstract I the paper, we cosder the probem o dstrbutg arge-sze cotet to a xed set o odes. I cotrast wth the most exstg ed-system soutos to

More information

Maintenance Scheduling of Distribution System with Optimal Economy and Reliability

Maintenance Scheduling of Distribution System with Optimal Economy and Reliability Egeerg, 203, 5, 4-8 http://dx.do.org/0.4236/eg.203.59b003 Publshed Ole September 203 (http://www.scrp.org/joural/eg) Mateace Schedulg of Dstrbuto System wth Optmal Ecoomy ad Relablty Syua Hog, Hafeg L,

More information

Security Analysis of RAPP: An RFID Authentication Protocol based on Permutation

Security Analysis of RAPP: An RFID Authentication Protocol based on Permutation Securty Aalyss of RAPP: A RFID Authetcato Protocol based o Permutato Wag Shao-hu,,, Ha Zhje,, Lu Sujua,, Che Da-we, {College of Computer, Najg Uversty of Posts ad Telecommucatos, Najg 004, Cha Jagsu Hgh

More information

On formula to compute primes and the n th prime

On formula to compute primes and the n th prime Joural's Ttle, Vol., 00, o., - O formula to compute prmes ad the th prme Issam Kaddoura Lebaese Iteratoal Uversty Faculty of Arts ad ceces, Lebao Emal: ssam.addoura@lu.edu.lb amh Abdul-Nab Lebaese Iteratoal

More information

Banking (Early Repayment of Housing Loans) Order, 5762 2002 1

Banking (Early Repayment of Housing Loans) Order, 5762 2002 1 akg (Early Repaymet of Housg Loas) Order, 5762 2002 y vrtue of the power vested me uder Secto 3 of the akg Ordace 94 (hereafter, the Ordace ), followg cosultato wth the Commttee, ad wth the approval of

More information

ROULETTE-TOURNAMENT SELECTION FOR SHRIMP DIET FORMULATION PROBLEM

ROULETTE-TOURNAMENT SELECTION FOR SHRIMP DIET FORMULATION PROBLEM 28-30 August, 2013 Sarawak, Malaysa. Uverst Utara Malaysa (http://www.uum.edu.my ) ROULETTE-TOURNAMENT SELECTION FOR SHRIMP DIET FORMULATION PROBLEM Rosshary Abd. Rahma 1 ad Razam Raml 2 1,2 Uverst Utara

More information

OPTIMAL KNOWLEDGE FLOW ON THE INTERNET

OPTIMAL KNOWLEDGE FLOW ON THE INTERNET İstabul Tcaret Üverstes Fe Blmler Dergs Yıl: 5 Sayı:0 Güz 006/ s. - OPTIMAL KNOWLEDGE FLOW ON THE INTERNET Bura ORDİN *, Urfat NURİYEV ** ABSTRACT The flow roblem ad the mmum sag tree roblem are both fudametal

More information

Sequences and Series

Sequences and Series Secto 9. Sequeces d Seres You c thk of sequece s fucto whose dom s the set of postve tegers. f ( ), f (), f (),... f ( ),... Defto of Sequece A fte sequece s fucto whose dom s the set of postve tegers.

More information

How To Value An Annuity

How To Value An Annuity Future Value of a Auty After payg all your blls, you have $200 left each payday (at the ed of each moth) that you wll put to savgs order to save up a dow paymet for a house. If you vest ths moey at 5%

More information

ISyE 512 Chapter 7. Control Charts for Attributes. Instructor: Prof. Kaibo Liu. Department of Industrial and Systems Engineering UW-Madison

ISyE 512 Chapter 7. Control Charts for Attributes. Instructor: Prof. Kaibo Liu. Department of Industrial and Systems Engineering UW-Madison ISyE 512 Chapter 7 Cotrol Charts for Attrbutes Istructor: Prof. Kabo Lu Departmet of Idustral ad Systems Egeerg UW-Madso Emal: klu8@wsc.edu Offce: Room 3017 (Mechacal Egeerg Buldg) 1 Lst of Topcs Chapter

More information

Curve Fitting and Solution of Equation

Curve Fitting and Solution of Equation UNIT V Curve Fttg ad Soluto of Equato 5. CURVE FITTING I ma braches of appled mathematcs ad egeerg sceces we come across epermets ad problems, whch volve two varables. For eample, t s kow that the speed

More information

Fault Tree Analysis of Software Reliability Allocation

Fault Tree Analysis of Software Reliability Allocation Fault Tree Aalyss of Software Relablty Allocato Jawe XIANG, Kokch FUTATSUGI School of Iformato Scece, Japa Advaced Isttute of Scece ad Techology - Asahda, Tatsuokuch, Ishkawa, 92-292 Japa ad Yaxag HE Computer

More information

n. We know that the sum of squares of p independent standard normal variables has a chi square distribution with p degrees of freedom.

n. We know that the sum of squares of p independent standard normal variables has a chi square distribution with p degrees of freedom. UMEÅ UNIVERSITET Matematsk-statstska sttutoe Multvarat dataaalys för tekologer MSTB0 PA TENTAMEN 004-0-9 LÖSNINGSFÖRSLAG TILL TENTAMEN I MATEMATISK STATISTIK Multvarat dataaalys för tekologer B, 5 poäg.

More information

Cyber Journals: Multidisciplinary Journals in Science and Technology, Journal of Selected Areas in Telecommunications (JSAT), January Edition, 2011

Cyber Journals: Multidisciplinary Journals in Science and Technology, Journal of Selected Areas in Telecommunications (JSAT), January Edition, 2011 Cyber Jourals: Multdscplary Jourals cece ad Techology, Joural of elected Areas Telecommucatos (JAT), Jauary dto, 2011 A ovel rtual etwork Mappg Algorthm for Cost Mmzg ZHAG hu-l, QIU Xue-sog tate Key Laboratory

More information

The impact of service-oriented architecture on the scheduling algorithm in cloud computing

The impact of service-oriented architecture on the scheduling algorithm in cloud computing Iteratoal Research Joural of Appled ad Basc Sceces 2015 Avalable ole at www.rjabs.com ISSN 2251-838X / Vol, 9 (3): 387-392 Scece Explorer Publcatos The mpact of servce-oreted archtecture o the schedulg

More information

M. Salahi, F. Mehrdoust, F. Piri. CVaR Robust Mean-CVaR Portfolio Optimization

M. Salahi, F. Mehrdoust, F. Piri. CVaR Robust Mean-CVaR Portfolio Optimization M. Salah, F. Mehrdoust, F. Pr Uversty of Gula, Rasht, Ira CVaR Robust Mea-CVaR Portfolo Optmzato Abstract: Oe of the most mportat problems faced by every vestor s asset allocato. A vestor durg makg vestmet

More information

Green Master based on MapReduce Cluster

Green Master based on MapReduce Cluster Gree Master based o MapReduce Cluster Mg-Zh Wu, Yu-Chag L, We-Tsog Lee, Yu-Su L, Fog-Hao Lu Dept of Electrcal Egeerg Tamkag Uversty, Tawa, ROC Dept of Electrcal Egeerg Tamkag Uversty, Tawa, ROC Dept of

More information

STOCHASTIC approximation algorithms have several

STOCHASTIC approximation algorithms have several IEEE TRANSACTIONS ON INFORMATION THEORY, VOL 60, NO 10, OCTOBER 2014 6609 Trackg a Markov-Modulated Statoary Degree Dstrbuto of a Dyamc Radom Graph Mazyar Hamd, Vkram Krshamurthy, Fellow, IEEE, ad George

More information

Load Balancing Control for Parallel Systems

Load Balancing Control for Parallel Systems Proc IEEE Med Symposum o New drectos Cotrol ad Automato, Chaa (Grèce),994, pp66-73 Load Balacg Cotrol for Parallel Systems Jea-Claude Heet LAAS-CNRS, 7 aveue du Coloel Roche, 3077 Toulouse, Frace E-mal

More information

FINANCIAL MATHEMATICS 12 MARCH 2014

FINANCIAL MATHEMATICS 12 MARCH 2014 FINNCIL MTHEMTICS 12 MRCH 2014 I ths lesso we: Lesso Descrpto Make use of logarthms to calculate the value of, the tme perod, the equato P1 or P1. Solve problems volvg preset value ad future value autes.

More information

Report 52 Fixed Maturity EUR Industrial Bond Funds

Report 52 Fixed Maturity EUR Industrial Bond Funds Rep52, Computed & Prted: 17/06/2015 11:53 Report 52 Fxed Maturty EUR Idustral Bod Fuds From Dec 2008 to Dec 2014 31/12/2008 31 December 1999 31/12/2014 Bechmark Noe Defto of the frm ad geeral formato:

More information

Statistical Pattern Recognition (CE-725) Department of Computer Engineering Sharif University of Technology

Statistical Pattern Recognition (CE-725) Department of Computer Engineering Sharif University of Technology I The Name of God, The Compassoate, The ercful Name: Problems' eys Studet ID#:. Statstcal Patter Recogto (CE-725) Departmet of Computer Egeerg Sharf Uversty of Techology Fal Exam Soluto - Sprg 202 (50

More information

Agent-based modeling and simulation of multiproject

Agent-based modeling and simulation of multiproject Aget-based modelg ad smulato of multproject schedulg José Alberto Araúzo, Javer Pajares, Adolfo Lopez- Paredes Socal Systems Egeerg Cetre (INSISOC) Uversty of Valladold Valladold (Spa) {arauzo,pajares,adolfo}ssoc.es

More information

RUSSIAN ROULETTE AND PARTICLE SPLITTING

RUSSIAN ROULETTE AND PARTICLE SPLITTING RUSSAN ROULETTE AND PARTCLE SPLTTNG M. Ragheb 3/7/203 NTRODUCTON To stuatos are ecoutered partcle trasport smulatos:. a multplyg medum, a partcle such as a eutro a cosmc ray partcle or a photo may geerate

More information

USEFULNESS OF BOOTSTRAPPING IN PORTFOLIO MANAGEMENT

USEFULNESS OF BOOTSTRAPPING IN PORTFOLIO MANAGEMENT USEFULNESS OF BOOTSTRAPPING IN PORTFOLIO MANAGEMENT Radovaov Bors Faculty of Ecoomcs Subotca Segedsk put 9-11 Subotca 24000 E-mal: radovaovb@ef.us.ac.rs Marckć Aleksadra Faculty of Ecoomcs Subotca Segedsk

More information

Credibility Premium Calculation in Motor Third-Party Liability Insurance

Credibility Premium Calculation in Motor Third-Party Liability Insurance Advaces Mathematcal ad Computatoal Methods Credblty remum Calculato Motor Thrd-arty Lablty Isurace BOHA LIA, JAA KUBAOVÁ epartmet of Mathematcs ad Quattatve Methods Uversty of ardubce Studetská 95, 53

More information

Optimal replacement and overhaul decisions with imperfect maintenance and warranty contracts

Optimal replacement and overhaul decisions with imperfect maintenance and warranty contracts Optmal replacemet ad overhaul decsos wth mperfect mateace ad warraty cotracts R. Pascual Departmet of Mechacal Egeerg, Uversdad de Chle, Caslla 2777, Satago, Chle Phoe: +56-2-6784591 Fax:+56-2-689657 rpascual@g.uchle.cl

More information

Bayesian Network Representation

Bayesian Network Representation Readgs: K&F 3., 3.2, 3.3, 3.4. Bayesa Network Represetato Lecture 2 Mar 30, 20 CSE 55, Statstcal Methods, Sprg 20 Istructor: Su-I Lee Uversty of Washgto, Seattle Last tme & today Last tme Probablty theory

More information

On Savings Accounts in Semimartingale Term Structure Models

On Savings Accounts in Semimartingale Term Structure Models O Savgs Accouts Semmartgale Term Structure Models Frak Döberle Mart Schwezer moeyshelf.com Techsche Uverstät Berl Bockehemer Ladstraße 55 Fachberech Mathematk, MA 7 4 D 6325 Frakfurt am Ma Straße des 17.

More information

Speeding up k-means Clustering by Bootstrap Averaging

Speeding up k-means Clustering by Bootstrap Averaging Speedg up -meas Clusterg by Bootstrap Averagg Ia Davdso ad Ashw Satyaarayaa Computer Scece Dept, SUNY Albay, NY, USA,. {davdso, ashw}@cs.albay.edu Abstract K-meas clusterg s oe of the most popular clusterg

More information

Automated Alignment and Extraction of Bilingual Ontology for Cross-Language Domain-Specific Applications

Automated Alignment and Extraction of Bilingual Ontology for Cross-Language Domain-Specific Applications Automated Agmet ad Extracto of gua Otoogy for Cross-Laguage Doma-Specfc Appcatos Ju-Feg Yeh, Chug-Hse Wu, Mg-Ju Che ad Lag-Chh Yu Departmet of Computer Scece ad Iformato Egeerg Natoa Cheg Kug Uversty,

More information

Contention-Free Periodic Message Scheduler Medium Access Control in Wireless Sensor / Actuator Networks

Contention-Free Periodic Message Scheduler Medium Access Control in Wireless Sensor / Actuator Networks Coteto-Free Perodc Message Sceduler Medum Access Cotrol Wreless Sesor / Actuator Networks Tomas W. Carley ECE Departmet Uversty of Marylad tcarley@eg.umd.edu Moussa A. Ba Embedded Researc Solutos mba@embeddedzoe.com

More information

Conversion of Non-Linear Strength Envelopes into Generalized Hoek-Brown Envelopes

Conversion of Non-Linear Strength Envelopes into Generalized Hoek-Brown Envelopes Covero of No-Lear Stregth Evelope to Geeralzed Hoek-Brow Evelope Itroducto The power curve crtero commoly ued lmt-equlbrum lope tablty aaly to defe a o-lear tregth evelope (relatohp betwee hear tre, τ,

More information

Mathematics of Finance

Mathematics of Finance CATE Mathematcs of ace.. TODUCTO ths chapter we wll dscuss mathematcal methods ad formulae whch are helpful busess ad persoal face. Oe of the fudametal cocepts the mathematcs of face s the tme value of

More information

MDM 4U PRACTICE EXAMINATION

MDM 4U PRACTICE EXAMINATION MDM 4U RCTICE EXMINTION Ths s a ractce eam. It does ot cover all the materal ths course ad should ot be the oly revew that you do rearato for your fal eam. Your eam may cota questos that do ot aear o ths

More information

10/19/2011. Financial Mathematics. Lecture 24 Annuities. Ana NoraEvans 403 Kerchof AnaNEvans@virginia.edu http://people.virginia.

10/19/2011. Financial Mathematics. Lecture 24 Annuities. Ana NoraEvans 403 Kerchof AnaNEvans@virginia.edu http://people.virginia. Math 40 Lecture 24 Autes Facal Mathematcs How ready do you feel for the quz o Frday: A) Brg t o B) I wll be by Frday C) I eed aother week D) I eed aother moth Aa NoraEvas 403 Kerchof AaNEvas@vrga.edu http://people.vrga.edu/~as5k/

More information

A two-stage stochastic mixed-integer program modelling and hybrid solution approach to portfolio selection problems

A two-stage stochastic mixed-integer program modelling and hybrid solution approach to portfolio selection problems A two-stage stochastc mxed-teger program modellg ad hybrd soluto approach to portfolo selecto problems Fag He, Rog Qu The Automated Schedulg, Optmsato ad Plag (ASAP) Group, School of Computer Scece The

More information

Projection model for Computer Network Security Evaluation with interval-valued intuitionistic fuzzy information. Qingxiang Li

Projection model for Computer Network Security Evaluation with interval-valued intuitionistic fuzzy information. Qingxiang Li Iteratoal Joural of Scece Vol No7 05 ISSN: 83-4890 Proecto model for Computer Network Securty Evaluato wth terval-valued tutostc fuzzy formato Qgxag L School of Software Egeerg Chogqg Uversty of rts ad

More information

Measuring the Quality of Credit Scoring Models

Measuring the Quality of Credit Scoring Models Measur the Qualty of Credt cor Models Mart Řezáč Dept. of Matheatcs ad tatstcs, Faculty of cece, Masaryk Uversty CCC XI, Edurh Auust 009 Cotet. Itroducto 3. Good/ad clet defto 4 3. Measur the qualty 6

More information

DECISION MAKING WITH THE OWA OPERATOR IN SPORT MANAGEMENT

DECISION MAKING WITH THE OWA OPERATOR IN SPORT MANAGEMENT ESTYLF08, Cuecas Meras (Meres - Lagreo), 7-9 de Septembre de 2008 DECISION MAKING WITH THE OWA OPERATOR IN SPORT MANAGEMENT José M. Mergó Aa M. Gl-Lafuete Departmet of Busess Admstrato, Uversty of Barceloa

More information

A Security-Oriented Task Scheduler for Heterogeneous Distributed Systems

A Security-Oriented Task Scheduler for Heterogeneous Distributed Systems A Securty-Oreted Tas Scheduler for Heterogeeous Dstrbuted Systems Tao Xe 1 ad Xao Q 2 1 Departmet of Computer Scece, Sa Dego State Uversty, Sa Dego, CA 92182, USA xe@cs.sdsu.edu 2 Departmet of Computer

More information

ANNEX 77 FINANCE MANAGEMENT. (Working material) Chief Actuary Prof. Gaida Pettere BTA INSURANCE COMPANY SE

ANNEX 77 FINANCE MANAGEMENT. (Working material) Chief Actuary Prof. Gaida Pettere BTA INSURANCE COMPANY SE ANNEX 77 FINANCE MANAGEMENT (Workg materal) Chef Actuary Prof. Gada Pettere BTA INSURANCE COMPANY SE 1 FUNDAMENTALS of INVESTMENT I THEORY OF INTEREST RATES 1.1 ACCUMULATION Iterest may be regarded as

More information

A PRACTICAL SOFTWARE TOOL FOR GENERATOR MAINTENANCE SCHEDULING AND DISPATCHING

A PRACTICAL SOFTWARE TOOL FOR GENERATOR MAINTENANCE SCHEDULING AND DISPATCHING West Ida Joural of Egeerg Vol. 30, No. 2, (Jauary 2008) Techcal aper (Sharma & Bahadoorsgh) 57-63 A RACTICAL SOFTWARE TOOL FOR GENERATOR MAINTENANCE SCHEDULING AND DISATCHING C. Sharma & S. Bahadoorsgh

More information