In the UC problem, we went a step further in assuming we could even remove a unit at any time if that would lower cost.

Size: px
Start display at page:

Download "In the UC problem, we went a step further in assuming we could even remove a unit at any time if that would lower cost."

Transcription

1 uel Schedulg (Chapter 6 of W&W.0 Itroducto I ecoomc dpatch we aumed the oly lmtato were o the output of the geerator: m g. h aumed that we could et ge to ay value we dered wth the rage, at ay tme, to acheve optmalty. I the UC problem, we wet a tep further aumg we could eve remove a ut at ay tme f that would lower cot. I both of thee problem, we were aumg that the fuel upply would alway exactly match our eed, that, we could tur o the fuel whe we wated t or tur t off whe we dd ot wat t, wthout regard to how much or how lttle fuel we mght be ug. h may ot alway be the cae. It may be poble that oe or more power plat are eergy-cotraed ome faho. h mea that the tegral of the plat power output over tme wll eed to be ether le tha a certa value or greater tha a certa value. h doe ot cotra power at ay partcular momet but t doe cotra the tme-tegrated power (eergy over a terval of tme. Sce eergy ca be uatfed term of amout of fuel (atural ga, coal, ol, cotrat o eergy a certa tme terval are euvalet to cotrat o fuel ue that tme terval. h why W&W-Ch 6 called Ge w/lmted Eergy Supply. It poble to have lower boud o fuel uage or upper boud o fuel uage. I hydro ytem, uch boud are dctated by water level reervor upplyg hydroelectrc power plat. Hydroelectrc faclte are made more complex, however, becaue may reervor ytem have coupled reervor uch that the eergy cotrat o oe hydro plat are coupled wth the eergy reuremet of the dowtream ad uptream hydro plat. We addre hydro chedulg uder the hydro-thermal coordato problem decrbed Chapter 7.

2 he problem of corporatg eergy cotrat for thermal ut referred to a the fuel chedulg (S problem. I the S problem, boud o fuel uage are dctated by the cotract the power plat ower mae wth the fuel uppler. Although th problem ha bee of teret for may year, referece [] artculate t the curret cotext of LM electrcty maret: I th cotext, t ow that a thermal plat that geerate oly whe pot prce are above t operatve cot ca meet t facal cotract oblgato wth a low effectve operatg cot: the plat doe ot operate bae load, beg hut dow durg the moth whe pot prce are low (ad beeft from pot maret purchae at very low cot. I other word, operatoal flexblty a very attractve charactertc for thermal plat the hydro-baed ytem. However, th operatoal flexblty, alog wth a low dverfcato of fuel maret, oppoto wth the eed of fuel producer whch have hgh fxed cot due to captal expedture developg producto ad traportato fratructure. A a coeuece, fuel upply agreemet are heavly tructured over cotract cludg tae-or-pay (o claue. hee are ut facal agreemet to reduce the volatlty of the fuel producer reveue ad (uually are ot aocated to coumpto oblgato. he o claue mpoe a atcpated purchae of a mmum amout of fuel (o a daly, mothly ad/or yearly ba, depedetly of t coumpto. Ofte, the amout of fuel bought but ot coumed vrtually tored (uder the form of credt for a pre-et perod. Durg th perod at aytme, the fuel ca be recovered by the plat. h ow a mae-up claue. Operatoal flexblty very attractve for thermal power plat ay LM maret, for the ame reao a tated here to tae advatage of LM prce varablty. uel producer do ot le up ad dow ue of ther fuel. h motvate o cotact. o may or may ot have mae-up claue whch tore what ot ued. o cotract wthout mae-up claue are commo.

3 here are ma type of fuel for thermal power plat, wth % of US electrcty upply: Coal (5% 008, 45% 00, 4% 0 atural ga (7% 008, 3% 00. 5% 0 etroleum (le tha % throughout Although petroleum ot ued at a gfcat level to upply power plat o a percetage ba of atoal eergy (<%, there are ome area where t a bt hgher (e.g., ew Eglad, 008, ol-fred ut compred 4.9% of total capacty ad % of eergy producto []. It clear from the above uote that uppler of thee fuel ca operate more effcetly f they ca obta tae-or-pay (o cotract, effectvely reducg ther ucertaty. A o cotract where the buyer pay for a mmum amout of fuel whether t tae or ot. he prce pad uder o-delvery may be eual to or le tha the prce pad for delvery. he o cotract eable the uppler to pla more precely regard to fuel producto. Mot cotract alo clude a celg o how much fuel ca be ued a certa perod..0 Mmzg cot for fleet wth a eergy cotraed ut We frt coder that a ower of a fleet of power plat, oe of whch are eergy cotraed, wat to mmze ther cot over a tme perod. he plat are bae-loaded ad o guarateed to be rug. otatoally, we follow W&W (ecto 6. accordg to: ( : fuel cot rate for ut durg terval. : power output for ut durg terval. R : total demad perod. : umber of hour th perod. 3

4 We dere to olve the followg optmzato problem: R m ubect to 0, (,..., where the obectve fucto the total cot (ot cot rate over all perod, ad the eualty cotrat the reuremet that ay oe perod, the upply mut eual demad. We are ot accoutg for geerator power producto lmt at th pot. ow let coder f there oe mache (or a group of mache for whch the ower ha egaged a o cotract wth a celg. Mathematcally, the mplet cae whe the mmum tae eual the celg. h mea that over the tme perod, the ut mut ue exactly a partcular amout of fuel. Let call th amout of fuel O. O wll have ut of RE ( raw eergy ad wll be dfferet for each fuel type: Coal: RE=to Ga: RE=ft 3 Ol: RE=bbl (barrel=4 gallo Let the ut uder the o cotract be ut =+ (o that we have ut wth ulmted fuel cotract. Defe a the fuel put rate for ut the th tme perod. Wherea ut of O are RE, the ut of are RE/hr. ote that a fucto of,.e., = (. RE/hr. How to get th fucto = (? ( 4

5 Defe K f a the eergy cotet of fuel, MBU/RE. ypcal value for K f are: uel K f (MBU/RE Coal athracte 5.64 MBU/to Coal - btumou 3.5 MBU/to Coal - lgte.7 MBU/to atural ga 0.00 MBU/ft 3 etroleum (tadard preure 5.88 MBU/bbl Aother way to th about th that the below uatte of fuel provde MBU: uel /K f (RE/MBU Other ut Coal athracte to/mbu 78lb/MBU Coal - btumou to/mbu 86lb/MBU Coal - lgte to/mbu 88lb/MBU atural ga 980 ft 3 /MBU 0ft 0ft 0ft/MBU (tadard preure etroleum 0.7 bbl/mbu 7 gallo/mbu Recall that H, the heat rate, MBU/MWhr ad that t a fucto of the power geerato level,.e., H=H(. he the fuel per MWhr wll be H( /K f, ad multplyg th by the power geerato level reult the fuel rate,.e., H( ( K ( f Bac to our mplet cae where the mmum tae eual the celg, the ummato of fuel ue by ut over all tme terval mut eual the fuel reuremet O, that O (3 5

6 Our ew problem, the, wll be exactly a our old problem a poed (, wth three excepto.. Add the cotrat (3.. Add fuel cot of our eergy-cotraed ut to the obectve fucto. 3. Iclude the power balace euato geerato correpodg to the eergy-cotraed ut, for each tme perod. herefore, the problem tatemet for the cotraed eergy problem become: m ubect to R O ( 0, (,..., he above problem tatemet ca be mplfed, however, by recogzg that the eergy-cotraed ut mut utlze exactly O of fuel, ad ce the cot of geerato domated by the fuel cot, the lat term the obectve fucto wll be a cotat. Sce cotat the obectve fucto do ot affect the deco to be made (.e., the oluto, a dcated by the deco varable, the we may ut remove that term, reultg the followg reved problem tatemet: m ubect to R O ( 0,,..., (4 (5 6

7 Let mae the followg defto, correpodg to the two eualty cotrat of (5: ( ( R ( 0, O 0,..., he, the problem tatemet ca be wrtte more cocely a: m ubect to ( ( he Lagraga become: L(,,, ( ( ( R 0, 0 O ( (,..., ( ow we ca wrte the optmalty codto. he frt optmalty codto we wll coder (6 (7 Sce $/hr, whe multpled by hr gve ut for the Lagraga of $. h mea λ mut be $/MW ad γ mut be $/(fuel-ut, where fuel-ut are ft 3 (for atural ga or to (for coal. (8 7

8 8 0 ( ( O R L (9a erformg the dfferetato, we obta 0 ( L (9b ow coder the optmalty codto 0 ( ( O R L (0a erformg the dfferetato, we obta 0 ( L (0a ally, the optmalty codto tag dervatve wth repect to the Lagrage multpler mply gve u thoe cotrat bac aga. I ummary, the optmalty codto reult the followg euato:

9 L me Iterval: me Iterval L : ( 0, ( 0,,...,,..., ( L me Iterval: me Iterval L : ( 0 ( 0 ( otce that f γ pecfed, the the euato of (, (, ad (3 from each tme perod are depedet ad each tme perod ca be olved by lambda-earch. L me Iterval: me Iterval L L : ( R R O (3 (4 We wll ext coder two dfferet way of how to olve thee euato. 3.0 uel chedulg oluto by gamma earch he approach here wll ue a er ad a outer earch mecham. he er earch mecham wll be a tadard lambda terato for each tme perod to provde u wth all geerato level for each tme perod. h earch wll be codtoed o a aumpto regardg cotraed fuel, repreeted by a 9

10 partcular value of gamma (γ. Each complete oluto of the er earch wll reult a total fuel uage correpodg to the choe value of gamma. he outer earch mecham wll be a earch o gamma to fd the certa value whch reult the fuel uage beg ut eual to the dered value O. h approach llutrated g. 6.3 of W&W. We wll how t, but frt we eed to recall how to perform the lambda-earch... Implemetato of the er earch mecham reure expreg the power output for each mache each tme terval a a fucto of lambda for that tme terval. rom (, we ca wrte for tme terval : L ( me Iterval : 0,,..., (5 If we aume ( uadratc, that ( a b c,..., (6 the ( b c,..., (7 Subttuto of (7 to (5 reult L b c 0,,..., (8 Solvg (8 for reult - b c,..., (8 h wll gve u the geerato level for all of the o-eergycotraed ut but ot for the eergy-cotraed ut. o obta the geerato level for the eergy-cotraed ut, we apply ( to tme terval. L ( 0 (9 0

11 We eed a expreo for (, but th ut euato (, repeated here for coveece: H( ( K ( f where K f the eergy cotet of fuel, MBU/RE (a we have ee. Recall the cot-rate curve (ee ote o cot curve wll be C C ( KH( (0 where K the prce of the put fuel $/MBU. Comparg ( ad (0, we ee that the expreo for ad C dffer oly by the cotat K f /K. he pot of th that the form of wll be the ame a the form of C. Sce C ut the cot-rate fucto for a ut, t wll geeral have a uadratc form. hu, we may repreet lewe,.e., for tme perod, ( a b c ( Oe hould be aware, however, that the coeffcet ( dffer from the coeffcet of ut cot-rate fucto by K f /K. Dfferetatg ( wth repect to reult ( b c ( Subttuto of ( to (9 reult L b c 0 (3 Solvg (3 for reult b c (4 I ummary, we have the followg euato to expre geerato level at each ut each tme perod: - b,..., (8 c

12 c b (4 h wll allow u to perform lambda terato. ote (4 a fucto of gamma. Oe thg rema, however. It wll be ueful to ow how to update lambda followg each terato. o obta a lambda update formula, frt recall the toppg crtero for lambda terato whether the geerato meet the load. h expreed by euato (3, whch, for terval, R 0 L (5 Solvg for R, we obta R (6 ow ubttute (8 ad (4 to (6 to obta R c b c b - (7 he we ca dfferetate (7 wth repect to λ to obta R c c (8 We may approxmate (8 a R c c (9 Solvg (9 for λ, we obta R c c (30

13 he Lambda terato method llutrated g.. Oberve that the flow chart of g. aume that gamma ow; alo the toppg crtero baed o the dfferece betwee demad & ge: R R GUESS γ = GUESS λ ew old - b,..., c c R c b c a b c R R o I R δ? Ye SO Ye I =? o =+ g. 3

14 So g. llutrate the er loop of the fuel chedulg oluto. What we eed to do ow to detfy how to adut gamma. o do that, let beg by recallg where gamma came from. We recall the Lagraga, (8, repeated here for coveece: L(,,, ( R ( ( O ( ( Here we ee that that γ the Lagrage multpler o the fuel cotrat. o get a lttle better feel for γ, recall the fuel cotrat (3: Recall ( ( O Subttuto of ( to (3 reult O (8 (3 a b c ( a b c (3 What we are after here the depedece of O o γ. o get th, recall (4: 4

15 b c (4 I wll ot go through the detal here, but rather ut artculate the procedure, whch to ubttute (4 to (3 ad the dfferetate to obta O / γ. he, mag the approxmato O O we may derve that O (3 I wll clude my had-wrtte dervato of (3 the appedx to thee ote. We mae three commet at th pot.. rom (3, we oberve that f γ>0, the γ alway oppote g to. hat, Icreae γ to decreae fuel uage of Ut. Decreae γ to creae fuel uage of Ut.. Aaly of ut (ee Lagraga dcate γ $/RE (recall RE Raw Eergy Ut. h dcate that γ le a fuel prce. h cotet wth commet # thg of ellg fuel, f we rae the prce, the demad decreae ad f we lower the prce, the demad creae. 3. We hould recogze, however, that γ ot the fuel prce. he fuel prce, alo wth ut of $/MBU, gve by K ee (0. So what γ? c 3 5

16 hg term of optmzato, a a Lagrage multpler, we ow that γ repreet the chage the obectve fucto of creag the rght-had-de of the correpodg cotrat by ut. Sad term of th problem, γ the addtoal cot of reurg the ue of oe addtoal RE ut of fuel at ut durg the ext tme perod. A teretg pot made (pg. 74 ad proved (Appedx of Chapter 7 that the addtoal ut of fuel could be reured ay tme terval. Sad aother way, γ cotat over tme. he chapter 7 appedx alo how, however, that γ wll vary a partcular tme perod f both the below are true. he problem clude cotrat o how much fuel ca be ued a partcular tme perod ( addto to the total amout of fuel to be ued over all tme perod, whch O. h ca happe for coal-fred plat due to the lmtato of coal tored o te. he cotrat for the partcular tme perod bdg. Ug (3, we are ow a poto to draw the etre fuelchedulg flow chart, a gve g. a. 6

17 GUESS γ = GUESS λ ew old - b,..., c c R c b c a b c R R o I R δ? Ye O O t Ye I =? o =+ I O <ε? Ye o SO c O 3 g. a 7

18 4.0 Compote geerator producto cot fucto (W&W, 6.3 Oe problem wth the oluto procedure troduced Secto 3.0 that a lambda terato mut be doe for every tme terval. If there are a large umber of ut (00, each lambda terato ca tae ome tme, ad of thee ca be very computatoal. We ugget a alterate procedure th ecto. he dea to obta a compote cot curve for the o-eergy-cotraed ut, ad the the lambda terato oly for two ut rather tha. Recall that whe we troduced the ut commtmet problem, we geerated a compote cot curve for 4 ut.we dd th aalytcally by ettg cremetal cot expreo eual, ug the power balace euato, ad olvg for each ut geerato level. h wa mey for four ut ad would be tractable for 00 ut. A alteratve procedure to develop the followg table, a et of umercal data for all o-fuel cotraed ut, =,,. λ S =Σ g S =Σ ( g λ m λ where d m m,,..., dg, d,,..., d gg,m g gg, ad each g the table foud from λ=d ( g /d g. If a ut ht a lmt, t output g ad cot ( g are held cotat. ote that the above value of λ are ued mply to get the compote cot fucto ad are ot the ame a the λ value the algorthm (whch are multpled by per e. (9b. A curve-fttg approach ca the be ued to obta the compote cot-rate fucto S ( S. Oce th doe, the the algorthm of 8

19 g. a appled, except that there oly o-eergy cotraed ut, a how g. b (yellow boxe dcated chage. GUESS γ = GUESS λ ew old S - b c S S R c c S b c a b c R R S o I R δ? Ye O O t Ye I =? o =+ Ye I O <ε? o SO c O 3 9

20 5.0 uel chedulg gradet oluto for optmalty Recall the optmalty codto from the Lagraga. Repeatg (9b, L ( 0 (9b ad (0a, L ( 0 (0a Solvg for λ each of thee euato, we obta ( (33 ( (34 Euatg (33 ad (34, we obta ( ( (35 Solvg for γ reult ( ( (36 Oberve the umerator ad deomator of (36: umerator the Icremetal uel Cot ($/MW-hr for ofuel cotraed ut durg terval. Deomator Icremetal uel Rate (RE/MW-hr for the cotraed ut durg terval. Our above developmet how that, for optmalty, th rato mut be cotat for all tme terval =,,. h cotet wth our prevou obervato that γ hould be cotat over tme. We ca formulate a algorthm baed o th fact, a llutrated g. 3, adapted from g. 6.7a your text, but we eed a feable chedule. 0

21 GEERAE COMOSIE RODUCIO COS UCIO OBAI EASIBLE SCHEDULE (ROM IG. 4 SUCH HA O (,,..., ote #5 ad ec 6 decrbe g. 4 to obta a feable oluto. CALCULAE OAL COS O O-COSRAIED UIS: total CALCULAE γ OR ALL IERVALS ( / ( SELEC IERVALS HA GIVE MAX AD MI γ. HIS MEAS O SELEC + AD - SUCH HA γ IS MAXIMUM OR =+ AD MIIMUM OR =-. =(γ + -γ - 0 WHERE 0 IS A CHOSE SMALL SE ADJUS I IERVALS + AD -. ICREASE + O MAKE γ + DECREASE: = + / ; =+ DECREASE - O MAKE γ - ICREASE: = + / ; =- CALCULAE EW VALUES O γ + ad γ - CALCULAE total (ee ote O total ε? YES DOE g. 3: Gradet oluto (ote # tell why t gradet ote #3 expla the dmeoalty problem here. ote # derve the eceary expreo.

22 We mae four commet about the method llutrated g. 3.. Your W&W text dcate o pg. 83 that the method may be called gradet method becaue treated a a vector ad the γ value dcate the gradet of the obectve fucto wth repect to. You ca oberve that th the cae from (36, ug the compote cot-curve,.e., ( ( ( ( ad otg that t mut be the cae that S =-, o that ( ( ( ( (37 (38 howg that γ may be terpreted a a etvty of the chage obectve fucto to a chage the amout of fuel ued tme terval. If we th of all of a a vector, e.g., the we may wrte a the gradet to.

23 . he ext-to-lat tep the algorthm of g. 3 dcate CALCULAE total (ee ote. h repreet the chage total cot (ad ot the chage total cot rate correpodg to the adutmet fuel uage made the prevou tep of the algorthm ( ADJUS I IERVALS + ad -. h calculato doe baed o the followg: ( ( ( ( ( ( ( ( But S+ =- +, ad S- =- +. Mag approprate ubttuto reult ( ( ( ( ( ( We mplfy the otato here a follow: (39 ow recall that γ + too hgh ad γ - too low, o we eed to decreae γ + ad creae γ -, whch we do by creag + ad decreag -. he fuel creae + mut eual the fuel decreae -, therefore, ad recallg that the fuel rate, we have that the fuel creae gve by the followg value (choe to be the ame g a + +, whch mut be potve cotet wth the bullet above whch dcate we mut creae t+. (40 herefore,, ( ( (4 3

24 Subttutg (4 to (39 reult Brgg the - over to the other de, we get: (43 ad you ca recogze the left-had-de a total that reured by the ext-to-lat tep the algorthm of g. 3. Commet: If the algorthm to coverge, that, f the total get maller wth each terato, the the left-had-de of (43 mut be egatve. We ee th mut be the cae by pectg the rghthad-de of (43 ce wa choe potve (ee (40 ad ce γ + >γ - by defto. Commet: If all tme terval are choe of eual durato,.e., f + = -, the (43 become (44 (4 3. he flow chart tep =(γ + -γ - 0 WHERE 0 IS A CHOSE SMALL SE ot dmeoally correct a t tad, becaue gamma ha ut of $/RE, ad whe multpled by RE, gve $, cotet wth the above dcuo regardg (43. You ca aume, however, that the relato really =[(γ + -γ - /][ 0 ], where the ha the ame ut a γ. he we oberve that f Δ 0 ha ut of RE, the o wll Δ. Bacally, th relato ut tellg u that f we wat to correct two terval - ad + for ther fuel (or water uage, we hould chooe a amout of fuel (or water to hft that proportoal to the dfferece betwee the two terval gamma value. 4

25 4. Oberve that toppg crtero to chec to ee f total chage gfcatly. 5. he ecod tep the algorthm of g. 3 dcate that t aume a feable (but ot ecearly optmal chedule that the fuel ue reuremet met ad the geerato dpatch of each tme terval locally optmal meag that t would be the optmal dpatch f we codered oly that tme terval. he problem at had : from where do we obta a feable chedule? h the topc of the ext ecto. 6.0 uel chedulg gradet oluto for feablty h approach llutrated g. 4. 5

26 GEERAE COMOSIE RODUCIO COS UCIO OBAI EASIBLE SCHEDULE IGORIG UEL COSRAI. BES AROACH IS O SOLVE ECOOMIC DISACH OR EACH ERIOD. ( (,,..., CALCULAE OAL UEL USED BY UI ' O CALCULAE γ OR ALL IERVALS ( / ( O (potve ID * WIH MI γ AD DECREASE, ICREASE S, O DECREASE UEL USE: = - for =* O - O <ε? O O - O <0? YES YES (egatve DOE (Go to g. 3. ID * WIH MAX γ AD ICREASE, DECREASE S, O ICREASE UEL USE: = + for =* CALCULAE γ OR =* ( / g. 4 ( 6

27 wo mportat obervato may be made from g. 4:. he ecod bloc from the top dcate that the algorthm beg wth a feable chedule for the problem wthout the fuel cotrat. he bet way to obta th from a ecoomc dpatch for each perod.. he thrd bloc obta the fuel ued by the partcular choe chedule. h computed by (3, repeated here for coveece: O a b c (3 Your W&W text provde a example fuel chedulg problem, whch olved by gamma earch (Example 6B, pg ad by the gradet approach (Example 6C, pg leae revew thee two example ad ow how to wor them. [] R. Chabar, M. erera, S. Gravlle, L. Barroo, ad. Ilad, Optmzato of uel Cotract Maagemet ad Mateace Schedulg for hermal lat uder rce Ucertaty, roc. of the ower Sytem Coferece ad Expoto, Oct. 9-ov, 006. [] H. Chao, Itegrato of atural Ga ad Electrcty ew Eglad ad the ret of US, preetato at the 008 AEX Coferece Sydey, Autrala, October 3-4,

Supply Chain Management Chapter 5: Application of ILP. Unified optimization methodology. Beun de Haas

Supply Chain Management Chapter 5: Application of ILP. Unified optimization methodology. Beun de Haas Supply Cha Maagemet Chapter 5: Ufed Optmzato Methodology for Operatoal Plag Problem What to do whe ILP take too much computato tme? Applcato of ILP Tmetable Dutch Ralway (NS) Bu ad drver chedulg at Coeo,

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

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

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

Swarm Based Truck-Shovel Dispatching System in Open Pit Mine Operations

Swarm Based Truck-Shovel Dispatching System in Open Pit Mine Operations Swarm Baed Truck-Shovel Dpatchg Sytem Ope Pt Me Operato Yaah Br, W. Scott Dubar ad Alla Hall Departmet of Mg ad Meral Proce Egeerg Uverty of Brth Columba, Vacouver, B.C., Caada Emal: br@mg.ubc.ca Abtract

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

Data Analysis Toolkit #10: Simple linear regression Page 1

Data Analysis Toolkit #10: Simple linear regression Page 1 Data Aaly Toolkt #0: mple lear regreo Page mple lear regreo the mot commoly ued techque f determg how oe varable of teret the repoe varable affected by chage aother varable the explaaty varable. The term

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

hal-00092005, version 2-12 Mar 2008

hal-00092005, version 2-12 Mar 2008 Author maucrpt, publhed "6th IFAC Sympoum o Fault Detecto, Supervo ad Safety of Techcal Procee, Safeproce'06, Beg : Cha (2006)" ODDS ALGORITHM -BASED OPPORTUNITY-TRIGGERED PREVENTIVE MAINTENANCE WITH PRODUCTION

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

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

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

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

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

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

Analysis of Two-Echelon Perishable Inventory System with Direct and Retrial demands

Analysis of Two-Echelon Perishable Inventory System with Direct and Retrial demands O Joural of Mathematc (O-JM) e-: 78-578 p-: 9-765X. Volume 0 ue 5 Ver. (ep-oct. 04) 5-57 www.oroural.org aly of Two-chelo erhable vetory ytem wth rect ad etral demad M. amehpad C.eryaamy K. Krha epartmet

More information

Finito: A Faster, Permutable Incremental Gradient Method for Big Data Problems

Finito: A Faster, Permutable Incremental Gradient Method for Big Data Problems Fto: A Fater, Permutable Icremetal Gradet Method or Bg ata Problem Aaro J. eazo Tbéro S. Caetao Jut omke NICTA ad Autrala Natoal Uverty AARON.FAZIO@ANU.U.AU TIBRIO.CATANO@NICTA.COM.AU JUSTIN.OMK@NICTA.COM.AU

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

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

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

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

A general sectional volume equation for classical geometries of tree stem

A general sectional volume equation for classical geometries of tree stem Madera y Boque 6 (2), 2:89-94 89 NOTA TÉCNICA A geeral ectoal volume equato for clacal geometre of tree tem Ua ecuacó geeral para el volume de la eccó de la geometría cláca del troco de lo árbole Gldardo

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

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

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

3.6. Metal-Semiconductor Field Effect Transistor (MESFETs)

3.6. Metal-Semiconductor Field Effect Transistor (MESFETs) .6. Metal-Semcouctor Fel Effect rator (MESFE he Metal-Semcouctor-Fel-Effect-rator (MESFE cot of a couctg chael potoe betwee a ource a ra cotact rego a how the Fgure.6.1. he carrer flow from ource to ra

More information

The Time Value of Money

The Time Value of Money The Tme Value of Moey 1 Iversemet Optos Year: 1624 Property Traded: Mahatta Islad Prce : $24.00, FV of $24 @ 6%: FV = $24 (1+0.06) 388 = $158.08 bllo Opto 1 0 1 2 3 4 5 t ($519.37) 0 0 0 0 $1,000 Opto

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

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

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

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

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

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

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 Analysis of Development of Insurance Contract Premiums of General Liability Insurance in the Business Insurance Risk

The Analysis of Development of Insurance Contract Premiums of General Liability Insurance in the Business Insurance Risk The Aalyss of Developmet of Isurace Cotract Premums of Geeral Lablty Isurace the Busess Isurace Rsk the Frame of the Czech Isurace Market 1998 011 Scetfc Coferece Jue, 10. - 14. 013 Pavla Kubová Departmet

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

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

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

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

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

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

GRADUATION PROJECT REPORT

GRADUATION PROJECT REPORT SPAM Flter School of Publc Admtrato Computer Stude Program GRADUATION PROJECT REPORT 2007-I-A02 SPAM Flter Project group leader: Project group member: Supervor: Aeor: Academc year (emeter): MCCS390 Graduato

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

Confidence Intervals for Linear Regression Slope

Confidence Intervals for Linear Regression Slope Chapter 856 Cofidece Iterval for Liear Regreio Slope Itroductio Thi routie calculate the ample ize eceary to achieve a pecified ditace from the lope to the cofidece limit at a tated cofidece level for

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

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

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

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

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

Online Tuning of Two Degrees of Freedom Fractional Order Control Loops

Online Tuning of Two Degrees of Freedom Fractional Order Control Loops DOI:.7694/bajece.49 Ole Tug of Two Degree of Freedom Fractoal Order Cotrol Loop A. Ate, ad C. Yeroglu Abtract Th paper preet ole tug of Two Degree of Freedom cotrol loop wth fractoal order proportoaltegraldervatve

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

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

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

Credit Risk Evaluation of Online Supply Chain Finance Based on Third-party B2B E-commerce Platform: an Exploratory Research Based on China s Practice

Credit Risk Evaluation of Online Supply Chain Finance Based on Third-party B2B E-commerce Platform: an Exploratory Research Based on China s Practice Iteratoal Joural of u- ad e- Servce, Scece ad Techology Vol.8, No.5 (2015, pp.93-104 http://dx.do.org/10.14257/juet.2015.8.5.09 Credt Rk Evaluato of Ole Supply Cha Face Baed o Thrd-party B2B E-commerce

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

Network dimensioning for elastic traffic based on flow-level QoS

Network dimensioning for elastic traffic based on flow-level QoS Network dmesog for elastc traffc based o flow-level QoS 1(10) Network dmesog for elastc traffc based o flow-level QoS Pas Lassla ad Jorma Vrtamo Networkg Laboratory Helsk Uversty of Techology Itroducto

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

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

Report 05 Global Fixed Income

Report 05 Global Fixed Income Report 05 Global Fxed Icome From Dec 1999 to Dec 2014 31/12/1999 31 December 1999 31/12/2014 Rep05, Computed & Prted: 17/06/2015 11:24 New Performace Idcator (01/01/12) 100% Barclays Aggregate Global Credt

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

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

Reinsurance and the distribution of term insurance claims

Reinsurance and the distribution of term insurance claims Resurace ad the dstrbuto of term surace clams By Rchard Bruyel FIAA, FNZSA Preseted to the NZ Socety of Actuares Coferece Queestow - November 006 1 1 Itroducto Ths paper vestgates the effect of resurace

More information

Report 19 Euroland Corporate Bonds

Report 19 Euroland Corporate Bonds Rep19, Computed & Prted: 17/06/2015 11:38 Report 19 Eurolad Corporate Bods From Dec 1999 to Dec 2014 31/12/1999 31 December 1999 31/12/2014 Bechmark 100% IBOXX Euro Corp All Mats. TR Defto of the frm ad

More information

Online Modern Philosophy for Stability Detection Based on Critical Energy of Individual Machines

Online Modern Philosophy for Stability Detection Based on Critical Energy of Individual Machines Iteratoal Joural of Scetfc Reearch Egeerg Techology Volume 1, Iue 4, July-2015, ISSN (Ole): 2395-566X Ole oder Phloophy for Stablty Detecto Baed o Crtcal Eergy of Idvdual ache Wagdy. ANSOUR Emal: wagdy_brahm2010@yahoo.com

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

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

CIS603 - Artificial Intelligence. Logistic regression. (some material adopted from notes by M. Hauskrecht) CIS603 - AI. Supervised learning

CIS603 - Artificial Intelligence. Logistic regression. (some material adopted from notes by M. Hauskrecht) CIS603 - AI. Supervised learning CIS63 - Artfcal Itellgece Logstc regresso Vasleos Megalookoomou some materal adopted from otes b M. Hauskrecht Supervsed learg Data: D { d d.. d} a set of eamples d < > s put vector ad s desred output

More information

FINANCIAL FORMULAE. Amount of One or Future Value of One ($1, 1, 1, etc.)... 2. Present Value (or Present Worth) of One ($1, 1, 1, etc.)...

FINANCIAL FORMULAE. Amount of One or Future Value of One ($1, 1, 1, etc.)... 2. Present Value (or Present Worth) of One ($1, 1, 1, etc.)... Amout of Oe or Future Value of Oe ($,,, etc.)... 2 Preset Value (or Preset Worth) of Oe ($,,, etc.)... 2 Amout of Oe per Perod... 3 or Future Value of Oe per Perod Preset Value (or Preset Worth) of Oe

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

ANALYTICAL MODEL FOR TCP FILE TRANSFERS OVER UMTS. Janne Peisa Ericsson Research 02420 Jorvas, Finland. Michael Meyer Ericsson Research, Germany

ANALYTICAL MODEL FOR TCP FILE TRANSFERS OVER UMTS. Janne Peisa Ericsson Research 02420 Jorvas, Finland. Michael Meyer Ericsson Research, Germany ANALYTICAL MODEL FOR TCP FILE TRANSFERS OVER UMTS Jae Pesa Erco Research 4 Jorvas, Flad Mchael Meyer Erco Research, Germay Abstract Ths paper proposes a farly complex model to aalyze the performace of

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

Report 06 Global High Yield Bonds

Report 06 Global High Yield Bonds Rep06, Computed & Prted: 17/06/2015 11:25 Report 06 Global Hgh Yeld Bods From Dec 2000 to Dec 2014 31/12/2000 31 December 1999 31/12/2014 New Bechmark (01/01/13) 80% Barclays Euro HY Ex Facals 3% Capped

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

TI-83, TI-83 Plus or TI-84 for Non-Business Statistics

TI-83, TI-83 Plus or TI-84 for Non-Business Statistics TI-83, TI-83 Plu or TI-84 for No-Buie Statitic Chapter 3 Eterig Data Pre [STAT] the firt optio i already highlighted (:Edit) o you ca either pre [ENTER] or. Make ure the curor i i the lit, ot o the lit

More information

Beta. A Statistical Analysis of a Stock s Volatility. Courtney Wahlstrom. Iowa State University, Master of School Mathematics. Creative Component

Beta. A Statistical Analysis of a Stock s Volatility. Courtney Wahlstrom. Iowa State University, Master of School Mathematics. Creative Component Beta A Statstcal Aalyss of a Stock s Volatlty Courtey Wahlstrom Iowa State Uversty, Master of School Mathematcs Creatve Compoet Fall 008 Amy Froelch, Major Professor Heather Bolles, Commttee Member Travs

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

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

A Parallel Transmission Remote Backup System

A Parallel Transmission Remote Backup System 2012 2d Iteratoal Coferece o Idustral Techology ad Maagemet (ICITM 2012) IPCSIT vol 49 (2012) (2012) IACSIT Press, Sgapore DOI: 107763/IPCSIT2012V495 2 A Parallel Trasmsso Remote Backup System Che Yu College

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

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

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

A Novel Resource Pricing Mechanism based on Multi-Player Gaming Model in Cloud Environments

A Novel Resource Pricing Mechanism based on Multi-Player Gaming Model in Cloud Environments 1574 JOURNAL OF SOFTWARE, VOL. 9, NO. 6, JUNE 2014 A Novel Resource Prcg Mechasm based o Mult-Player Gamg Model Cloud Evromets Tea Zhag, Peg Xao School of Computer ad Commucato, Hua Isttute of Egeerg,

More information

The Present Value of an Annuity

The Present Value of an Annuity Module 4.4 Page 492 of 944. Module 4.4: The Preset Value of a Auty Here we wll lear about a very mportat formula: the preset value of a auty. Ths formula s used wheever there s a seres of detcal paymets

More information

A New Bayesian Network Method for Computing Bottom Event's Structural Importance Degree using Jointree

A New Bayesian Network Method for Computing Bottom Event's Structural Importance Degree using Jointree , pp.277-288 http://dx.do.org/10.14257/juesst.2015.8.1.25 A New Bayesa Network Method for Computg Bottom Evet's Structural Importace Degree usg Jotree Wag Yao ad Su Q School of Aeroautcs, Northwester Polytechcal

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

The paper presents Constant Rebalanced Portfolio first introduced by Thomas

The paper presents Constant Rebalanced Portfolio first introduced by Thomas Itroducto The paper presets Costat Rebalaced Portfolo frst troduced by Thomas Cover. There are several weakesses of ths approach. Oe s that t s extremely hard to fd the optmal weghts ad the secod weakess

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

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

RQM: A new rate-based active queue management algorithm

RQM: A new rate-based active queue management algorithm : A ew rate-based actve queue maagemet algorthm Jeff Edmods, Suprakash Datta, Patrck Dymod, Kashf Al Computer Scece ad Egeerg Departmet, York Uversty, Toroto, Caada Abstract I ths paper, we propose a ew

More information

We present a new approach to pricing American-style derivatives that is applicable to any Markovian setting

We present a new approach to pricing American-style derivatives that is applicable to any Markovian setting MANAGEMENT SCIENCE Vol. 52, No., Jauary 26, pp. 95 ss 25-99 ess 526-55 6 52 95 forms do.287/msc.5.447 26 INFORMS Prcg Amerca-Style Dervatves wth Europea Call Optos Scott B. Laprse BAE Systems, Advaced

More information

THE EQUILIBRIUM MODELS IN OLIGOPOLY ELECTRICITY MARKET

THE EQUILIBRIUM MODELS IN OLIGOPOLY ELECTRICITY MARKET Iteratoal Coferee The Euroea Eletrty Market EEM-4 etember -, 4, Lodz, Polad Proeedg Volume,. 35-4 THE EQUILIBRIUM MODEL IN OLIGOPOLY ELECTRICITY MARKET Agezka Wyłomańka Wrolaw Uverty of Tehology Wrolaw

More information

How do bookmakers (or FdJ 1 ) ALWAYS manage to win?

How do bookmakers (or FdJ 1 ) ALWAYS manage to win? How do bookakers (or FdJ ALWAYS aage to w? Itroducto otatos & varables Bookaker's beeft eected value 4 4 Bookaker's strateges5 4 The hoest bookaker 6 4 "real lfe" bookaker 6 4 La FdJ 8 5 How ca we estate

More information

Performance Attribution. Methodology Overview

Performance Attribution. Methodology Overview erformace Attrbuto Methodology Overvew Faba SUAREZ March 2004 erformace Attrbuto Methodology 1.1 Itroducto erformace Attrbuto s a set of techques that performace aalysts use to expla why a portfolo's performace

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

Load Balancing Algorithm based Virtual Machine Dynamic Migration Scheme for Datacenter Application with Optical Networks

Load Balancing Algorithm based Virtual Machine Dynamic Migration Scheme for Datacenter Application with Optical Networks 0 7th Iteratoal ICST Coferece o Commucatos ad Networkg Cha (CHINACOM) Load Balacg Algorthm based Vrtual Mache Dyamc Mgrato Scheme for Dataceter Applcato wth Optcal Networks Xyu Zhag, Yogl Zhao, X Su, Ruyg

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

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

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

TESTING AND SECURITY IN DISTRIBUTED ECONOMETRIC APPLICATIONS REENGINEERING VIA SOFTWARE EVOLUTION

TESTING AND SECURITY IN DISTRIBUTED ECONOMETRIC APPLICATIONS REENGINEERING VIA SOFTWARE EVOLUTION TESTING AND SECURITY IN DISTRIBUTED ECONOMETRIC APPLICATIONS REENGINEERING VIA SOFTWARE EVOLUTION Cosm TOMOZEI 1 Assstat-Lecturer, PhD C. Vasle Alecsadr Uversty of Bacău, Romaa Departmet of Mathematcs

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