A Binary Quantum-behaved Particle Swarm Optimization Algorithm with Cooperative Approach
|
|
- Antonia Park
- 8 years ago
- Views:
Transcription
1 IJCSI Internatonal Journal of Computer Scence Issues, Vol., Issue, No, January 3 ISSN (Prnt): ISSN (Onlne): A Bnary Quantum-behave Partcle Swarm Optmzaton Algorthm wth Cooperatve Approach Jng Zhao,, Jun Sun an Wenbo Xu 3 School of Dgtal ea, Jangnan Unversty Wux, 4, Jangsu, Chna School of Informaton, Shanong Polytechnc Unversty, Jnan, 5353, Shanong, Chna 3 School of Internet of Thngs Engneerng, Jangnan Unversty Wux, 4, Jangsu, Chna Abstract A novel bnary Quantum-behave Partcle Swarm Optmzaton algorthm wth cooperatve approach () s ntrouce. In the propose algorthm, the upatng metho of partcle s prevous best poston an swarm s global best poston are performe n each menson of soluton vector to avo loss some components that have move closer to the global optmal soluton n the vector. Fve test functons are use to test the performance of. The results of experments show that the propose technque can ncrease versty of populaton an converge more raply than other bnary algorthms. Keywors: Quantum-behave Partcle Swarm Optmzaton, Bnary, Cooperatve Approach, Test Functons.. Introucton Partcle Swarm Optmzaton (PSO) s an evolutonary computaton technque evelope by Dr. Eberhart an Dr. Kenney n 995 [], nspre by socal behavor of br flockng or fsh schoolng. The optmal soluton s obtane by exchangng nformaton between nvuals. owever, the algorthm cannot converges to the global mnmum pont wth probablty one uner sutable conton []. Jun Sun et al have propose a global convergence-guarantee PSO algorthm [3], Quantum-behave Partcle Swarm Optmzaton (QPSO) algorthm, whch s nspre by quantum mechancs. It has been shown that QPSO outperforms PSO on several aspects, such as smple evoluton equatons, more few control parameters, fast convergence spee, smple operaton an so on [4,5]. In 997, Kenney propose the bnary verson of PSO () [6], an Jun Sun et al propose the bnary verson of QPSO () n 7 [7]. Ths paper wll focus on evelopng the bnary verson of QPSO wth cooperatve metho (). In the propose algorthm, each menson of partcle s new soluton vector replaces n turn the corresponng menson of partcle s prevous best poston an swarm s global best poston to calculate the ftness value. The rest structure of ths paper s as follows. In secton, a bref ntroucton of the s presente. The s escrbe n secton 3. Next, the novel s epcte n secton 4. Then the experment results are gven n secton 5. Fnally, the concluson s put forwar n secton 6.. Bnary Partcle Swarm Optmzaton In PSO, the populaton wth nvuals, whch s treate as a partcle, s calle a swarm X n the D- mensonal space. The poston vector an velocty vector of partcle at the generaton t represente as x t) ( x, x,, x ( )) an ( D t ( v ( t), v,, vd( t v )).The partcle moves accorng to the equatons: v ( t ) wv cr ( x ) () c r ( gbest x ) x ( t ) x v ( t ) () Where,,, ;,,, D, w s the nerta weght, whose value s typcally setup to vary lnearly from.9 to.4. c an c are calle the acceleraton coeffcents whch usually are set as c c. r an r are ranom number unformly strbute n (,).Vector (,,, D) s the best prevous poston of partcle wth the name personal best poston( ), whle the global best poston( gbest ), gbest ( gbest, gbest,, gbest D), s the best partcle poston among all the partcles n the populaton. Copyrght (c) 3 Internatonal Journal of Computer Scence Issues. All Rghts Reserve.
2 IJCSI Internatonal Journal of Computer Scence Issues, Vol., Issue, No, January 3 ISSN (Prnt): ISSN (Onlne): In [6,8], Eq. (3) replaces Eq. (). f ran () S( V )) then X else X (3) ( Where S (v) s a sgmo lmtng transformaton functon( s( v) v ( e ) ), an ran () s a ranom number selecte from a unform strbuton n (,). 3. Bnary Quantum-behave Partcle Swarm Optmzaton 3. Quantum-behave Partcle Swarm Optmzaton In PSO algorthm, the state of partcle s epcte by ts poston vector an velocty vector, whch etermne the trajectory of the partcle. The partcle moves along a etermne trajectory n Newtonan mechancs, but ths s not the case n quantum mechancs. In quantum worl, the term trajectory s meanngless, because poston an velocty of a partcle cannot be etermne smultaneously accorng to uncertanty prncple. Therefore, f nvual partcles n a PSO system have quantum behavor, the PSO algorthm s boun to work n a fferent fashon. In quantum tme-space framework, Jun Sun et al. ntrouce QPSO algorthm. The equatons are as follows: mbest (4) (,,, D) p x ( ) gbest (5) ( t ) p mbest x *ln( ) (6) u where s a ranom number unformly strbute n (,). mbest s mean best poston of the populaton. Parameter s calle the Contracton-Expanson coeffcent, whch can be tune to control the convergence spee of the algorthm. From the results of stochastc smulaton [9], t can be conclue that n QPSO, when. 78, the partcles wll converge. In the process of teraton, s ece by the ranom number, when t s bgger than.5, mnus sgn ( - ) s propose, others plus sgn ( + ) s propose. 3. Bnary Quantum-behave Partcle Swarm Optmzaton In ths secton, a screte bnary verson of QPSO () s propose. Because the teraton equatons of QPSO are far fferent from those of PSO, the methoology of oes not apply to QPSO. In QPSO, there are no veloctes an trajectores concepts but poston an stance. In, the poston of the partcle s represente as a bnary strng. The stance s efne as the ammng stance between two bnary strngs. That s X Y ( X, Y) (7) Where X an Y are two bnary strngs an represent two postons. The functon () s to get the ammng stance between X an Y. The ammng stance s the count of bts fferent n the two strngs. The jth bt of the mbest s etermne by the states of the jth bts of all partcles n. If more partcles take on at the jth bt of ther own, the jth bts of mbest wll be ; otherwse the bt wll be. owever, f half of the partcles take on at the jth bt of ther, the jth bt of mbest wll be set ranomly to be or, wth probablty.5 for ether state. In, the pont operaton on mult-pont crossover operaton on p s obtane by crossover an gbest. Frstly make one-pont or an gbest to generate two offsprng. Then ranomly select one of the offsprng an output t as the pont Conser teratve Eq. (6) an transform t as b ( x, p ) ( x, mbest) ln( ) (8) u We can obtan the new strng x by the transformaton n whch each bt n p s mutate wth the probablty compute by b l c (9) b f l Where l s the length of the th menson of partcle. In the process of teraton, f ran () c, the corresponng bt n the poston of partcle wll be reverse, otherwse remans t. p. Copyrght (c) 3 Internatonal Journal of Computer Scence Issues. All Rghts Reserve.
3 IJCSI Internatonal Journal of Computer Scence Issues, Vol., Issue, No, January 3 ISSN (Prnt): ISSN (Onlne): Wth the above efnton an mofcatons of teratve equatons, the algorthm s escrbe as the followng proceure: Step Intalze an array of bnary bts for all partcles, partcle s personal best postons an swarm s global best poston gbest ; Step For each partcle, etermne the mbest an get a stochastc poston p by exertng crossover operaton on an gbest ; Step 3 For each menson, compute the mutaton probablty c an then upate the partcle s new poston x by c ; Step 4 Evaluate the objectve functon value of the partcle, an compare t wth the objectve functon value of an gbest. If the current objectve functon value s better than that of an gbest, then upate an gbest ; Step 5 Repeat step ~4 untl the stoppng crteron s satsfe or reaches the gven maxmal teraton. 4. Bnary Quantum-behave Partcle Swarm Optmzaton wth Cooperatve Approach As an escrbe, each partcle represents a complete soluton vector for the objectve functon f ( X ) f X, X,, X N. Each upate step s also performe on a full D-mensonal vector. Then t may be appear the possblty that some menson n the soluton vector have move closer to the global optmum, whle others move away from the global optmum. Whereas the objectve functon value of the soluton vector s worse than the former value. an take the new soluton vector for a complete vector an neglect the eterorate components urng the teratons. As long as the current objectve functon value s better than the former value, then upate an gbest. Therefore, the current soluton vector can be gve up n next teraton an the valuable nformaton of the soluton vector s lost unknowngly. In orer to make full use of the benefcal nformaton, the cooperatve metho [,] s ntrouce to. In the propose metho, we expect that the operaton can avo the unesrable behavor, whch s a case of takng two steps forwar (some menson mprove), an one step back (some menson eterorate). 4. Cooperatve Approach We expect that once for every tme a component n the vector has been upate, resultng n much qucker feeback. Thus, a cooperatve metho for ong just ths s presente. In the new metho each menson of the new soluton vector replaces n turn the corresponng menson of an gbest, an then compare the new objectve functon value to ece whether to upate an gbest. The process s as follows: Step For each partcle, ntalze c ; cgbest gbest, Step For each menson of partcle, replace the menson of c an cgbest by the corresponng menson of the partcle; Step 3 Evaluate the new objectve functon value of c an cgbest, an compare them wth the objectve functon value of an gbest. If the current objectve functon value s better than that of an gbest, then upate an gbest ; Step 4 Repeat step ~3 untl all the menson of the partcle s compare. 4. Wth above mofcatons, the teraton process of s escrbe step-by-step below. Step Intalze an array of bnary bts for all partcles, partcle s personal best postons an swarm s global best poston gbest ; Step Upate the partcle s new poston x by ; Step 3 Evaluate the objectve functon value of the partcle, an compare them wth the objectve functon value of an gbest. If the current objectve functon value s better than that of an gbest, then upate an gbest ; Step 4 Use cooperatve strategy to upate an gbest ; Copyrght (c) 3 Internatonal Journal of Computer Scence Issues. All Rghts Reserve.
4 IJCSI Internatonal Journal of Computer Scence Issues, Vol., Issue, No, January 3 ISSN (Prnt): ISSN (Onlne): Step 5 Repeat step ~4 untl the stoppng crteron s satsfe or reaches the gven maxmal teraton. The propose algorthm tres to mprove convergence precson by comparng each menson of soluton vector. It must exten the search space an then ncrease the tme consumpton. Two aaptve control methos are propose. Frstly, the cooperatve strategy s aopte n a certan nterval. In our metho, t set to 5. Then the cooperatve strategy s performe when the bt of the partcle s fferent from the corresponng bt of an gbest. 5. Experments In ths secton, the performance of algorthm s teste on the followng fve fferent stanar functons [7] to be maxmze. Then the results are compare wth an. 3 f ( X ) x ( 5. x 5.) f ( X ) (( x (.48 x x ).48) f3( X ) 5 ( x x x3 x4 x5) x Z, ( 5. 5.) x 3 ( x ) 4 f 4( X ) 48. x (.8 x.8) 5 f5( X ) 5. 6 ( ) j j x aj a ( x ) In the numercal experments, the algorthms parameters settngs are escrbe as follow: for, the acceleraton coeffcents are set to c c an the nerta weght w s ecreasng lnearly from.9 to.4. In experments for an, the value of s.4 []. All experments are run 5 nepenent tmes respectvely wth a populaton of, an partcles on an Intel(R) Xeon(R) GB RA computer wth the software envronment of ATLAB9a. All the algorthms termnate when the number of teratons succees. The best ftness value (BFV), maxmum value an mnmum value are recore after the algorthm termnates at each run. The performance of all the algorthms s ) evaluate by average BFV (Avg. BFV) an Stanar Devaton (St. Dev.). All the measurements are lste on Table. Fg. llustrates the convergence process of average BFV of three algorthms over 5 runs wth partcles on fve test functons. The optma of functon f, whose ftness value s, can be fn out by, an. As can be seen from Table, the average BFV an St. Dev. of s best. An outperforms. As of soluton qualty, an wth partcles make successful searches out of 5 tral runs, whereas fn out the optma for 7 tmes. An the corresponng tmes s 4, 3 an respectvely wth partcles. When the populaton number s, the optma are foun out for 9, an 4 tmes corresponng wth, an. On the functon f, all the algorthms can be foun the optmum ftness value. owever generates best average BFV an St. Dev.. An takes secon place. As can be seen from Table, has the worst performance than other two algorthms wth partcles. Note that the St. Dev. of wth partcles s better than that of. The thr functon f 3 s a smple nteger functon wth an optmum of., an wth partcles ht the optma for 5 tmes out of 5 runs. an have better qualty of soluton than wth an partcles. In orer to measure the average ftness value over the entre populaton, Gaussan nose s ntrouce nto f 4 functon. In ths functon, the average BFV of s nferor to but superor to. owever the St. Dev. of s the best results. The last functon f 5 has an optmum 5. All the algorthms can be foun out the best value wth an partlces s able to ht the optmum beyon 47 tmes out of 5 runs. The number of successful searches of s better than. owever the average BFV an St. Dev. of s nferor to. As s llustrate n Fg., we can see that the effectveness of the propose. can converge to the optmum more raply than an on three functons except f an f 5. On f, converges more quckly but generates worse soluton than. On f 5, converges raply than other two Copyrght (c) 3 Internatonal Journal of Computer Scence Issues. All Rghts Reserve.
5 IJCSI Internatonal Journal of Computer Scence Issues, Vol., Issue, No, January 3 ISSN (Prnt): ISSN (Onlne): algorthms at the early stage of runnng, but excees soon an generates a slghtly better soluton. Compare wth an, expermental results show the effectveness of the propose. Functon f f f 3 f 4 f 5 Partcles Table : Results of, an on fve testng functons ean (St.Dev.) AX (IN) ean (St.Dev.) AX (IN) ean (St.Dev.) AX (IN) functon f functon f teratons teratons (a) f (b) f Copyrght (c) 3 Internatonal Journal of Computer Scence Issues. All Rghts Reserve.
6 IJCSI Internatonal Journal of Computer Scence Issues, Vol., Issue, No, January 3 ISSN (Prnt): ISSN (Onlne): functon f3 6 functon f teratons (c) f 3 () f 4 5 functon f5 teratons teratons (e) f 5 Fg. The convergence process of three algorthms wth partcles. 6. Conclusons In, an mprovement n two components wll overrule a potentally goo value for a sngle component. In ths paper, a screte bnary verson of Quantumbehave Partcle Swarm Optmzaton algorthm wth cooperatve metho () s ntrouce to mprove the unesrable behavor by ecomposng the soluton vector. In the propose algorthm, each menson upate of partcle can fee back to personal best postons an swarm best poston. The results of experment have showe that the algorthm performs better than other algorthm on global convergence an has stronger ablty to escape from the local optmal soluton urng the search process. owever t can be exten the search space wth the ncreasng complexty of the problem, tme consumpton s the man efcency of. References [] Kenney J., an Eberhart R., "Partcle Swarm Optmzaton", n IEEE Internatonal Conference on Neural Networks, 995, Vol.4, pp [] Frans Van Den Bergh, "An Analyss of Partcle Swarm Optmzers", Ph.D. thess, Unversty of Pretora, South Afrca,. [3] Jun Sun, Bn Feng, an Wenbo Xu, "Partcle Swarm Optmzaton wth Partcles avng Quantum Behavor", n IEEE Congress on Evolutonary Computaton, 4, Vol., pp [4] Jun Sun, We Fang, Xaojun Wu, Vasle Palae, an Wenbo Xu, "Quantum-behave Partcle Swarm Optmzaton: Analyss of Invual Partcle Behavor an Parameter Selecton", Evolutonary Computaton, Vol., No. 3,, pp [5] We Fang, Jun Sun, Yanru Dng, Xaojun Wu, an Wenbo Xu, "A Revew of Quantum-behave Partcle Swarm Optmzaton", IETE Techncal Revew, Vol.7, No.4,, pp Copyrght (c) 3 Internatonal Journal of Computer Scence Issues. All Rghts Reserve.
7 IJCSI Internatonal Journal of Computer Scence Issues, Vol., Issue, No, January 3 ISSN (Prnt): ISSN (Onlne): [6] Kenney, J., an Eberhar, R. C, "A Dscrete Bnary Verson of the Partcles Swarm Algorthm". In IEEE Internatonal Conference on Systems, an an Cybernetcs, 997, Vol.5, pp [7] Jun Sun, Wenbo Xu, We Fang, an Zhle Cha, "Quantumbehave Partcle Swarm Optmzaton wth Bnary Encong", n Internatonal Conference on Aaptve an Natural Computng Algorthms, 7, Vol., pp [8] Seyye Al ashem,an Behrouz Nowrouzan, "A Novel Dscrete Partcle Swarm Optmzaton for FR FIR Dgtal Flters", Journal of Computers, Vol.7, No.6,, pp [9] Jun Sun, Xaojun Wu, Vasle Palae, We Fang, Cho-ong La, an Wenbo Xu, "Convergence Analyss an Improvements of Quantum-behave Partcle Swarm Optmzaton", Journal of Informaton Scence, Vol.93,, pp.8-3. [] Van en Bergh F., an Engelbrecht A. P., "A Cooperatve Approach to Partcle Swarm Optmzaton", IEEE Transactons on Evolutonary Computaton, Vol.8, No.3, 4, pp [] eh Neshat, Shma F. Yaz, Daneyal Yazan, an eh Sargolzae, "A New Cooperatve Algorthm Base on PSO an K-eans for Data Clusterng", Journal of Computers Scence, Vol.8, No.,, pp [] Jun Sun, "Partcle Swarm Optmzaton wth Partcles avng Quantum", Ph.D. thess, Jangnan Unversty, Wux, Chna, 9. Copyrght (c) 3 Internatonal Journal of Computer Scence Issues. All Rghts Reserve.
Patterns Antennas Arrays Synthesis Based on Adaptive Particle Swarm Optimization and Genetic Algorithms
IJCSI Internatonal Journal of Computer Scence Issues, Vol. 1, Issue 1, No 2, January 213 ISSN (Prnt): 1694-784 ISSN (Onlne): 1694-814 www.ijcsi.org 21 Patterns Antennas Arrays Synthess Based on Adaptve
More informationA hybrid global optimization algorithm based on parallel chaos optimization and outlook algorithm
Avalable onlne www.ocpr.com Journal of Chemcal and Pharmaceutcal Research, 2014, 6(7):1884-1889 Research Artcle ISSN : 0975-7384 CODEN(USA) : JCPRC5 A hybrd global optmzaton algorthm based on parallel
More informationExact GP Schema Theory for Headless Chicken Crossover and Subtree Mutation
Exact GP Schema Theory for Healess Chcken Crossover an Subtree Mutaton Rccaro Pol School of Computer Scence The Unversty of Brmngham Brmngham, B5 TT, UK R.Pol@cs.bham.ac.uk Ncholas F. McPhee Dvson of Scence
More informationDocument Clustering Analysis Based on Hybrid PSO+K-means Algorithm
Document Clusterng Analyss Based on Hybrd PSO+K-means Algorthm Xaohu Cu, Thomas E. Potok Appled Software Engneerng Research Group, Computatonal Scences and Engneerng Dvson, Oak Rdge Natonal Laboratory,
More informationMooring Pattern Optimization using Genetic Algorithms
6th World Congresses of Structural and Multdscplnary Optmzaton Ro de Janero, 30 May - 03 June 005, Brazl Moorng Pattern Optmzaton usng Genetc Algorthms Alonso J. Juvnao Carbono, Ivan F. M. Menezes Luz
More informationSOLVING CARDINALITY CONSTRAINED PORTFOLIO OPTIMIZATION PROBLEM BY BINARY PARTICLE SWARM OPTIMIZATION ALGORITHM
SOLVIG CARDIALITY COSTRAIED PORTFOLIO OPTIMIZATIO PROBLEM BY BIARY PARTICLE SWARM OPTIMIZATIO ALGORITHM Aleš Kresta Klíčová slova: optmalzace portfola, bnární algortmus rojení částc Key words: portfolo
More informationA Binary Particle Swarm Optimization Algorithm for Lot Sizing Problem
Journal o Economc and Socal Research 5 (2), -2 A Bnary Partcle Swarm Optmzaton Algorthm or Lot Szng Problem M. Fath Taşgetren & Yun-Cha Lang Abstract. Ths paper presents a bnary partcle swarm optmzaton
More informationThe Development of Web Log Mining Based on Improve-K-Means Clustering Analysis
The Development of Web Log Mnng Based on Improve-K-Means Clusterng Analyss TngZhong Wang * College of Informaton Technology, Luoyang Normal Unversty, Luoyang, 471022, Chna wangtngzhong2@sna.cn Abstract.
More informationAn Efficient Recovery Algorithm for Coverage Hole in WSNs
An Effcent Recover Algorthm for Coverage Hole n WSNs Song Ja 1,*, Wang Balng 1, Peng Xuan 1 School of Informaton an Electrcal Engneerng Harbn Insttute of Technolog at Weha, Shanong, Chna Automatc Test
More informationDEGREES OF EQUIVALENCE IN A KEY COMPARISON 1 Thang H. L., Nguyen D. D. Vietnam Metrology Institute, Address: 8 Hoang Quoc Viet, Hanoi, Vietnam
DEGREES OF EQUIVALECE I A EY COMPARISO Thang H. L., guyen D. D. Vetnam Metrology Insttute, Aress: 8 Hoang Quoc Vet, Hano, Vetnam Abstract: In an nterlaboratory key comparson, a ata analyss proceure for
More informationCluster Analysis. Cluster Analysis
Cluster Analyss Cluster Analyss What s Cluster Analyss? Types of Data n Cluster Analyss A Categorzaton of Maor Clusterng Methos Parttonng Methos Herarchcal Methos Densty-Base Methos Gr-Base Methos Moel-Base
More informationInvestigation of Modified Bee Colony Algorithm with Particle and Chaos Theory
Internatonal Journal of Control and Automaton, pp. 311-3 http://dx.do.org/10.1457/jca.015.8..30 Investgaton of Modfed Bee Colony Algorthm wth Partcle and Chaos Theory Guo Cheng Shangluo College, Zhangye,
More informationA New Task Scheduling Algorithm Based on Improved Genetic Algorithm
A New Task Schedulng Algorthm Based on Improved Genetc Algorthm n Cloud Computng Envronment Congcong Xong, Long Feng, Lxan Chen A New Task Schedulng Algorthm Based on Improved Genetc Algorthm n Cloud Computng
More informationA COPMARISON OF PARTICLE SWARM OPTIMIZATION AND THE GENETIC ALGORITHM
A COPMARISON OF PARTICLE SWARM OPTIMIZATION AND THE GENETIC ALGORITHM Rana Hassan * Babak Cohanm Olver de Weck Massachusetts Insttute of Technology, Cambrdge, MA, 39 Gerhard Venter Vanderplaats Research
More informationThe Design of Efficiently-Encodable Rate-Compatible LDPC Codes
The Desgn of Effcently-Encoable Rate-Compatble LDPC Coes Jaehong Km, Atya Ramamoorthy, Member, IEEE, an Steven W. McLaughln, Fellow, IEEE Abstract We present a new class of rregular low-ensty party-check
More informationGlobal Optimization Algorithms with Application to Non-Life Insurance
Global Optmzaton Algorthms wth Applcaton to Non-Lfe Insurance Problems Ralf Kellner Workng Paper Char for Insurance Economcs Fredrch-Alexander-Unversty of Erlangen-Nürnberg Verson: June 202 GLOBAL OPTIMIZATION
More informationSciences Shenyang, Shenyang, China.
Advanced Materals Research Vols. 314-316 (2011) pp 1315-1320 (2011) Trans Tech Publcatons, Swtzerland do:10.4028/www.scentfc.net/amr.314-316.1315 Solvng the Two-Obectve Shop Schedulng Problem n MTO Manufacturng
More informationTHE LOAD PLANNING PROBLEM FOR LESS-THAN-TRUCKLOAD MOTOR CARRIERS AND A SOLUTION APPROACH. Professor Naoto Katayama* and Professor Shigeru Yurimoto*
7th Internatonal Symposum on Logstcs THE LOAD PLAIG PROBLEM FOR LESS-THA-TRUCKLOAD MOTOR CARRIERS AD A SOLUTIO APPROACH Professor aoto Katayama* an Professor Shgeru Yurmoto* * Faculty of Dstrbuton an Logstcs
More informationAn Interest-Oriented Network Evolution Mechanism for Online Communities
An Interest-Orented Network Evoluton Mechansm for Onlne Communtes Cahong Sun and Xaopng Yang School of Informaton, Renmn Unversty of Chna, Bejng 100872, P.R. Chna {chsun,yang}@ruc.edu.cn Abstract. Onlne
More informationIncentive Compatible Mechanisms for Group Ticket Allocation in Software Maintenance Services
14th Asa-Pacfc Software Engneerng Conference Incentve Compatble Mechansms for Group Tcket Allocaton n Software Mantenance Servces Karthk Subban, Ramakrshnan Kannan IBM R Ina Software Lab, EGL D Block,
More informationOn the Optimal Control of a Cascade of Hydro-Electric Power Stations
On the Optmal Control of a Cascade of Hydro-Electrc Power Statons M.C.M. Guedes a, A.F. Rbero a, G.V. Smrnov b and S. Vlela c a Department of Mathematcs, School of Scences, Unversty of Porto, Portugal;
More informationIntelligent Method for Cloud Task Scheduling Based on Particle Swarm Optimization Algorithm
Unversty of Nzwa, Oman December 9-11, 2014 Page 39 THE INTERNATIONAL ARAB CONFERENCE ON INFORMATION TECHNOLOGY (ACIT2014) Intellgent Method for Cloud Task Schedulng Based on Partcle Swarm Optmzaton Algorthm
More informationDecomposition Methods for Large Scale LP Decoding
Decomposton Methos for Large Scale LP Decong Sharth Barman Xshuo Lu Stark Draper Benjamn Recht Abstract Felman et al. IEEE Trans. Inform. Theory, Mar. 2005) showe that lnear programmng LP) can be use to
More information"Research Note" APPLICATION OF CHARGE SIMULATION METHOD TO ELECTRIC FIELD CALCULATION IN THE POWER CABLES *
Iranan Journal of Scence & Technology, Transacton B, Engneerng, ol. 30, No. B6, 789-794 rnted n The Islamc Republc of Iran, 006 Shraz Unversty "Research Note" ALICATION OF CHARGE SIMULATION METHOD TO ELECTRIC
More informationComparison of Weighted Sum Fitness Functions for PSO Optimization of Wideband Medium-gain Antennas
54 ZHOGKU MA, G. A. E. VAEBOSCH, COMPARISO OF WEIGHTE SUM FITESS FUCTIOS FOR PSO Comparson of Weghted Sum Ftness Functons for PSO Optmzaton of Wdeband Medum-gan Antennas Zhongkun MA, Guy A. E. VAEBOSCH
More informationA Secure Password-Authenticated Key Agreement Using Smart Cards
A Secure Password-Authentcated Key Agreement Usng Smart Cards Ka Chan 1, Wen-Chung Kuo 2 and Jn-Chou Cheng 3 1 Department of Computer and Informaton Scence, R.O.C. Mltary Academy, Kaohsung 83059, Tawan,
More informationDistributed Strategic Learning with Application to Network Security
Amercan Control Conference on O'Farrell Street San Francsco CA USA June 9 - July Dstrbute Strategc Learnng wth Applcaton to Network Securty Quanyan Zhu Hamou Tembne an Tamer Başar Abstract We conser n
More informationLITERATURE REVIEW: VARIOUS PRIORITY BASED TASK SCHEDULING ALGORITHMS IN CLOUD COMPUTING
LITERATURE REVIEW: VARIOUS PRIORITY BASED TASK SCHEDULING ALGORITHMS IN CLOUD COMPUTING 1 MS. POOJA.P.VASANI, 2 MR. NISHANT.S. SANGHANI 1 M.Tech. [Software Systems] Student, Patel College of Scence and
More informationEfficient Algorithms for Computing the Triplet and Quartet Distance Between Trees of Arbitrary Degree
Effcent Algorthms for omputng the Trplet an Quartet Dstance Between Trees of Arbtrary Degree Gerth Støltng Broal, Rolf Fagerberg Thomas Malun hrstan N. S. Peersen, Anreas San, Abstract The trplet an quartet
More informationOn the Optimal Marginal Rate of Income Tax
On the Optmal Margnal Rate of Income Tax Gareth D Myles Insttute for Fscal Stues an Unversty of Exeter June 999 Abstract: The paper shows that n the quas-lnear moel of ncome taxaton, the optmal margnal
More informationHybrid-Learning Methods for Stock Index Modeling
Hybrd-Learnng Methods for Stock Index Modelng 63 Chapter IV Hybrd-Learnng Methods for Stock Index Modelng Yuehu Chen, Jnan Unversty, Chna Ajth Abraham, Chung-Ang Unversty, Republc of Korea Abstract The
More informationData Broadcast on a Multi-System Heterogeneous Overlayed Wireless Network *
JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 24, 819-840 (2008) Data Broadcast on a Mult-System Heterogeneous Overlayed Wreless Network * Department of Computer Scence Natonal Chao Tung Unversty Hsnchu,
More informationSCHEDULING OF CONSTRUCTION PROJECTS BY MEANS OF EVOLUTIONARY ALGORITHMS
SCHEDULING OF CONSTRUCTION PROJECTS BY MEANS OF EVOLUTIONARY ALGORITHMS Magdalena Rogalska 1, Wocech Bożeko 2,Zdzsław Heduck 3, 1 Lubln Unversty of Technology, 2- Lubln, Nadbystrzycka 4., Poland. E-mal:rogalska@akropols.pol.lubln.pl
More informationOptimal Choice of Random Variables in D-ITG Traffic Generating Tool using Evolutionary Algorithms
Optmal Choce of Random Varables n D-ITG Traffc Generatng Tool usng Evolutonary Algorthms M. R. Mosav* (C.A.), F. Farab* and S. Karam* Abstract: Impressve development of computer networks has been requred
More informationA Load-Balancing Algorithm for Cluster-based Multi-core Web Servers
Journal of Computatonal Informaton Systems 7: 13 (2011) 4740-4747 Avalable at http://www.jofcs.com A Load-Balancng Algorthm for Cluster-based Mult-core Web Servers Guohua YOU, Yng ZHAO College of Informaton
More informationDynamic Constrained Economic/Emission Dispatch Scheduling Using Neural Network
Dynamc Constraned Economc/Emsson Dspatch Schedulng Usng Neural Network Fard BENHAMIDA 1, Rachd BELHACHEM 1 1 Department of Electrcal Engneerng, IRECOM Laboratory, Unversty of Djllal Labes, 220 00, Sd Bel
More informationAn algorithm of choosing LSPs in the MPLS network with unreliable links
Ireneusz OLSZESKI Unversty of Technology an Lfe Scences n Bygoszcz, Faculty of Telecommuncatons an Electrcal Engneerng An algorthm of choosng LSPs n the MPLS network wth unrelable lnks Streszczene. pracy
More informationAnts Can Schedule Software Projects
Ants Can Schedule Software Proects Broderck Crawford 1,2, Rcardo Soto 1,3, Frankln Johnson 4, and Erc Monfroy 5 1 Pontfca Unversdad Católca de Valparaíso, Chle FrstName.Name@ucv.cl 2 Unversdad Fns Terrae,
More informationPresent Values and Accumulations
Present Values an Accumulatons ANGUS S. MACDONALD Volume 3, pp. 1331 1336 In Encyclopea Of Actuaral Scence (ISBN -47-84676-3) Ete by Jozef L. Teugels an Bjørn Sunt John Wley & Sons, Lt, Chchester, 24 Present
More informationTesting and Debugging Resource Allocation for Fault Detection and Removal Process
Internatonal Journal of New Computer Archtectures and ther Applcatons (IJNCAA) 4(4): 93-00 The Socety of Dgtal Informaton and Wreless Communcatons, 04 (ISSN: 0-9085) Testng and Debuggng Resource Allocaton
More informationBlind Estimation of Transmit Power in Wireless Networks
Bln Estmaton of Transmt Power n Wreless Networks Murtaza Zafer (IBM Research), Bongjun Ko (IBM Research), Chatschk Bskan (IBM Research) an Ivan Ho (Imperal College, UK) Transmt-power Estmaton: Problem
More informationA General and Practical Datacenter Selection Framework for Cloud Services
212 IEEE Ffth Internatonal Conference on Clou Computng A General an Practcal Datacenter Selecton Framework for Clou Servces Hong Xu, Baochun L henryxu, bl@eecg.toronto.eu Department of Electrcal an Computer
More informationOptimal Provisioning of Resource in a Cloud Service
ISSN (Onlne): 169-081 95 Optmal Provsonng of Resource n a Cloud Servce Yee Mng Chen 1 Shn-Yng Tsa Department of Industral Engneerng and Management Yuan Ze Unversty 135 Yuan-Tung Rd. Chung-L Tao-Yuan Tawan
More informationA Genetic Programming Based Stock Price Predictor together with Mean-Variance Based Sell/Buy Actions
Proceedngs of the World Congress on Engneerng 28 Vol II WCE 28, July 2-4, 28, London, U.K. A Genetc Programmng Based Stock Prce Predctor together wth Mean-Varance Based Sell/Buy Actons Ramn Rajaboun and
More information行 政 院 國 家 科 學 委 員 會 補 助 專 題 研 究 計 畫 成 果 報 告 期 中 進 度 報 告
行 政 院 國 家 科 學 委 員 會 補 助 專 題 研 究 計 畫 成 果 報 告 期 中 進 度 報 告 畫 類 別 : 個 別 型 計 畫 半 導 體 產 業 大 型 廠 房 之 設 施 規 劃 計 畫 編 號 :NSC 96-2628-E-009-026-MY3 執 行 期 間 : 2007 年 8 月 1 日 至 2010 年 7 月 31 日 計 畫 主 持 人 : 巫 木 誠 共 同
More informationA heuristic task deployment approach for load balancing
Xu Gaochao, Dong Yunmeng, Fu Xaodog, Dng Yan, Lu Peng, Zhao Ja Abstract A heurstc task deployment approach for load balancng Gaochao Xu, Yunmeng Dong, Xaodong Fu, Yan Dng, Peng Lu, Ja Zhao * College of
More informationMaintenance Scheduling by using the Bi-Criterion Algorithm of Preferential Anti-Pheromone
Leonardo ournal of Scences ISSN 583-0233 Issue 2, anuary-une 2008 p. 43-64 Mantenance Schedulng by usng the B-Crteron Algorthm of Preferental Ant-Pheromone Trantafyllos MYTAKIDIS and Arstds VLACHOS Department
More informationResearch Article Enhanced Two-Step Method via Relaxed Order of α-satisfactory Degrees for Fuzzy Multiobjective Optimization
Hndaw Publshng Corporaton Mathematcal Problems n Engneerng Artcle ID 867836 pages http://dxdoorg/055/204/867836 Research Artcle Enhanced Two-Step Method va Relaxed Order of α-satsfactory Degrees for Fuzzy
More informationSolving Factored MDPs with Continuous and Discrete Variables
Solvng Factored MPs wth Contnuous and screte Varables Carlos Guestrn Berkeley Research Center Intel Corporaton Mlos Hauskrecht epartment of Computer Scence Unversty of Pttsburgh Branslav Kveton Intellgent
More informationEXAMPLE PROBLEMS SOLVED USING THE SHARP EL-733A CALCULATOR
EXAMPLE PROBLEMS SOLVED USING THE SHARP EL-733A CALCULATOR 8S CHAPTER 8 EXAMPLES EXAMPLE 8.4A THE INVESTMENT NEEDED TO REACH A PARTICULAR FUTURE VALUE What amount must you nvest now at 4% compoune monthly
More informationModule 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur
Module LOSSLESS IMAGE COMPRESSION SYSTEMS Lesson 3 Lossless Compresson: Huffman Codng Instructonal Objectves At the end of ths lesson, the students should be able to:. Defne and measure source entropy..
More informationForecasting the Demand of Emergency Supplies: Based on the CBR Theory and BP Neural Network
700 Proceedngs of the 8th Internatonal Conference on Innovaton & Management Forecastng the Demand of Emergency Supples: Based on the CBR Theory and BP Neural Network Fu Deqang, Lu Yun, L Changbng School
More informationOn the computation of the capital multiplier in the Fortis Credit Economic Capital model
On the computaton of the captal multpler n the Forts Cret Economc Captal moel Jan Dhaene 1, Steven Vuffel 2, Marc Goovaerts 1, Ruben Oleslagers 3 Robert Koch 3 Abstract One of the key parameters n the
More informationInformation Sciences
Informaton Scences 0 (013) 45 441 Contents lsts avalable at ScVerse ScenceDrect Informaton Scences journal homepage: www.elsever.com/locate/ns A hybrd method of fuzzy smulaton and genetc algorthm to optmze
More informationSoftware project management with GAs
Informaton Scences 177 (27) 238 241 www.elsever.com/locate/ns Software project management wth GAs Enrque Alba *, J. Francsco Chcano Unversty of Málaga, Grupo GISUM, Departamento de Lenguajes y Cencas de
More informationA Stigmergy Approach for Open Source Software Developer Community Simulation
A Stgmergy Approach for Open Source Software Developer Communty Smulaton Xaohu Cu, Justn Beaver, Jm Treawell an Thomas Potok Oak Rge Natonal Laboratory Oak Rge, TN 37831 Laura Pullum Lockhee Martn Corporaton
More informationLuby s Alg. for Maximal Independent Sets using Pairwise Independence
Lecture Notes for Randomzed Algorthms Luby s Alg. for Maxmal Independent Sets usng Parwse Independence Last Updated by Erc Vgoda on February, 006 8. Maxmal Independent Sets For a graph G = (V, E), an ndependent
More informationMining Feature Importance: Applying Evolutionary Algorithms within a Web-based Educational System
Mnng Feature Importance: Applyng Evolutonary Algorthms wthn a Web-based Educatonal System Behrouz MINAEI-BIDGOLI 1, and Gerd KORTEMEYER 2, and Wllam F. PUNCH 1 1 Genetc Algorthms Research and Applcatons
More informationAnswer: A). There is a flatter IS curve in the high MPC economy. Original LM LM after increase in M. IS curve for low MPC economy
4.02 Quz Solutons Fall 2004 Multple-Choce Questons (30/00 ponts) Please, crcle the correct answer for each of the followng 0 multple-choce questons. For each queston, only one of the answers s correct.
More informationAn efficient constraint handling methodology for multi-objective evolutionary algorithms
Rev. Fac. Ing. Unv. Antoqua N. 49. pp. 141-150. Septembre, 009 An effcent constrant handlng methodology for mult-objectve evolutonary algorthms Una metodología efcente para manejo de restrccones en algortmos
More informationHigh Performance Latent Dirichlet Allocation for Text Mining
Hgh Performance Latent Drchlet Allocaton for Text Mnng A thess submtte for Degree of Doctor of Phlosophy By Department of Electronc an Computer Engneerng School of Engneerng an Desgn Brunel Unversty September
More informationOptimal Bidding Strategies for Generation Companies in a Day-Ahead Electricity Market with Risk Management Taken into Account
Amercan J. of Engneerng and Appled Scences (): 8-6, 009 ISSN 94-700 009 Scence Publcatons Optmal Bddng Strateges for Generaton Companes n a Day-Ahead Electrcty Market wth Rsk Management Taken nto Account
More informationFeature selection for intrusion detection. Slobodan Petrović NISlab, Gjøvik University College
Feature selecton for ntruson detecton Slobodan Petrovć NISlab, Gjøvk Unversty College Contents The feature selecton problem Intruson detecton Traffc features relevant for IDS The CFS measure The mrmr measure
More informationVehicle Routing Problem with Time Windows for Reducing Fuel Consumption
3020 JOURNAL OF COMPUTERS, VOL. 7, NO. 12, DECEMBER 2012 Vehcle Routng Problem wth Tme Wndows for Reducng Fuel Consumpton Jn L School of Computer and Informaton Engneerng, Zhejang Gongshang Unversty, Hangzhou,
More informationProject Networks With Mixed-Time Constraints
Project Networs Wth Mxed-Tme Constrants L Caccetta and B Wattananon Western Australan Centre of Excellence n Industral Optmsaton (WACEIO) Curtn Unversty of Technology GPO Box U1987 Perth Western Australa
More informationResource Scheduling Scheme Based on Improved Frog Leaping Algorithm in Cloud Environment
Informaton technologes Resource Schedulng Scheme Based on Improved Frog Leapng Algorthm n Cloud Envronment Senbo Chen 1, 2 1 School of Computer Scence and Technology, Nanjng Unversty of Aeronautcs and
More informationImproved SVM in Cloud Computing Information Mining
Internatonal Journal of Grd Dstrbuton Computng Vol.8, No.1 (015), pp.33-40 http://dx.do.org/10.1457/jgdc.015.8.1.04 Improved n Cloud Computng Informaton Mnng Lvshuhong (ZhengDe polytechnc college JangSu
More informationA SURVEY ON REACTIVE POWER OPTIMIZATION AND VOLTAGE STABILITY IN POWER SYSTEMS
Internatonal Journal on Techncal and Physcal Problems of Engneerng (IJTPE) Publshed by Internatonal Organzaton of IOTPE ISSN 077-358 IJTPE Journal www.otpe.com jtpe@otpe.com March 014 Issue 18 Volume 6
More informationA Practical Study of Regenerating Codes for Peer-to-Peer Backup Systems
A Practcal Stuy of Regeneratng Coes for Peer-to-Peer Backup Systems Alessanro Dumnuco an Ernst Bersack EURECOM Sopha Antpols, France {umnuco,bersack}@eurecom.fr Abstract In strbute storage systems, erasure
More informationBlending Roulette Wheel Selection & Rank Selection in Genetic Algorithms
Internatonal Journal of Machne Learnng and Computng, Vol. 2, o. 4, August 2012 Blendng Roulette Wheel Selecton & Rank Selecton n Genetc Algorthms Rakesh Kumar, Senor Member, IACSIT and Jyotshree, Member,
More informationPAS: A Packet Accounting System to Limit the Effects of DoS & DDoS. Debish Fesehaye & Klara Naherstedt University of Illinois-Urbana Champaign
PAS: A Packet Accountng System to Lmt the Effects of DoS & DDoS Debsh Fesehaye & Klara Naherstedt Unversty of Illnos-Urbana Champagn DoS and DDoS DDoS attacks are ncreasng threats to our dgtal world. Exstng
More informationWhen Network Effect Meets Congestion Effect: Leveraging Social Services for Wireless Services
When Network Effect Meets Congeston Effect: Leveragng Socal Servces for Wreless Servces aowen Gong School of Electrcal, Computer and Energy Engeerng Arzona State Unversty Tempe, AZ 8587, USA xgong9@asuedu
More informationWatermark-based Provable Data Possession for Multimedia File in Cloud Storage
Vol.48 (CIA 014), pp.103-107 http://dx.do.org/10.1457/astl.014.48.18 Watermar-based Provable Data Possesson for Multmeda Fle n Cloud Storage Yongjun Ren 1,, Jang Xu 1,, Jn Wang 1,, Lmng Fang 3, Jeong-U
More informationJ. Parallel Distrib. Comput.
J. Parallel Dstrb. Comput. 71 (2011) 62 76 Contents lsts avalable at ScenceDrect J. Parallel Dstrb. Comput. journal homepage: www.elsever.com/locate/jpdc Optmzng server placement n dstrbuted systems n
More informationPortfolio Loss Distribution
Portfolo Loss Dstrbuton Rsky assets n loan ortfolo hghly llqud assets hold-to-maturty n the bank s balance sheet Outstandngs The orton of the bank asset that has already been extended to borrowers. Commtment
More informationForecasting the Direction and Strength of Stock Market Movement
Forecastng the Drecton and Strength of Stock Market Movement Jngwe Chen Mng Chen Nan Ye cjngwe@stanford.edu mchen5@stanford.edu nanye@stanford.edu Abstract - Stock market s one of the most complcated systems
More informationEnergy Efficient Coverage Optimization in Wireless Sensor Networks based on Genetic Algorithm
Unversal Journal of Communcatons and Network 3(4): 82-88, 2015 DOI: 10.13189/ujcn.2015.030402 http://www.hrpub.org Energy Effcent Coverage Optmzaton n Wreless Sensor Networks based on Genetc Algorthm Al
More informationIMPACT ANALYSIS OF A CELLULAR PHONE
4 th ASA & μeta Internatonal Conference IMPACT AALYSIS OF A CELLULAR PHOE We Lu, 2 Hongy L Bejng FEAonlne Engneerng Co.,Ltd. Bejng, Chna ABSTRACT Drop test smulaton plays an mportant role n nvestgatng
More informationA Novel Methodology of Working Capital Management for Large. Public Constructions by Using Fuzzy S-curve Regression
Novel Methodology of Workng Captal Management for Large Publc Constructons by Usng Fuzzy S-curve Regresson Cheng-Wu Chen, Morrs H. L. Wang and Tng-Ya Hseh Department of Cvl Engneerng, Natonal Central Unversty,
More informationUsing Multi-objective Metaheuristics to Solve the Software Project Scheduling Problem
Usng Mult-obectve Metaheurstcs to Solve the Software Proect Schedulng Problem Francsco Chcano Unversty of Málaga, Span chcano@lcc.uma.es Francsco Luna Unversty of Málaga, Span flv@lcc.uma.es Enrque Alba
More informationVehicle Detection and Tracking in Video from Moving Airborne Platform
Journal of Computatonal Informaton Systems 10: 12 (2014) 4965 4972 Avalable at http://www.jofcs.com Vehcle Detecton and Trackng n Vdeo from Movng Arborne Platform Lye ZHANG 1,2,, Hua WANG 3, L LI 2 1 School
More informationChapter 4 ECONOMIC DISPATCH AND UNIT COMMITMENT
Chapter 4 ECOOMIC DISATCH AD UIT COMMITMET ITRODUCTIO A power system has several power plants. Each power plant has several generatng unts. At any pont of tme, the total load n the system s met by the
More informationAn Analysis of Dynamic Severity and Population Size
An Analyss of Dynamc Severty and Populaton Sze Karsten Wecker Unversty of Stuttgart, Insttute of Computer Scence, Bretwesenstr. 2 22, 7565 Stuttgart, Germany, emal: Karsten.Wecker@nformatk.un-stuttgart.de
More informationRobotics and Computer-Integrated Manufacturing
Robotcs and Computer-Integrated Manufacturng 27 (2) 977 98 Contents lsts avalable at ScenceDrect Robotcs and Computer-Integrated Manufacturng journal homepage: www.elsever.com/locate/rcm Optmal desgn of
More informationNPAR TESTS. One-Sample Chi-Square Test. Cell Specification. Observed Frequencies 1O i 6. Expected Frequencies 1EXP i 6
PAR TESTS If a WEIGHT varable s specfed, t s used to replcate a case as many tmes as ndcated by the weght value rounded to the nearest nteger. If the workspace requrements are exceeded and samplng has
More informationA GENETIC ALGORITHM-BASED METHOD FOR CREATING IMPARTIAL WORK SCHEDULES FOR NURSES
82 Internatonal Journal of Electronc Busness Management, Vol. 0, No. 3, pp. 82-93 (202) A GENETIC ALGORITHM-BASED METHOD FOR CREATING IMPARTIAL WORK SCHEDULES FOR NURSES Feng-Cheng Yang * and We-Tng Wu
More informationDescriptive Models. Cluster Analysis. Example. General Applications of Clustering. Examples of Clustering Applications
CMSC828G Prncples of Data Mnng Lecture #9 Today s Readng: HMS, chapter 9 Today s Lecture: Descrptve Modelng Clusterng Algorthms Descrptve Models model presents the man features of the data, a global summary
More informationOptimization Model of Reliable Data Storage in Cloud Environment Using Genetic Algorithm
Internatonal Journal of Grd Dstrbuton Computng, pp.175-190 http://dx.do.org/10.14257/gdc.2014.7.6.14 Optmzaton odel of Relable Data Storage n Cloud Envronment Usng Genetc Algorthm Feng Lu 1,2,3, Hatao
More informationLearning with Imperfections A Multi-Agent Neural-Genetic Trading System. with Differing Levels of Social Learning
Proceedngs of the 4 IEEE Conference on Cybernetcs and Intellgent Systems Sngapore, 1-3 December, 4 Learnng wth Imperfectons A Mult-Agent Neural-Genetc Tradng System wth Dfferng Levels of Socal Learnng
More informationAnt Colony Optimization for Economic Generator Scheduling and Load Dispatch
Proceedngs of the th WSEAS Int. Conf. on EVOLUTIONARY COMPUTING, Lsbon, Portugal, June 1-18, 5 (pp17-175) Ant Colony Optmzaton for Economc Generator Schedulng and Load Dspatch K. S. Swarup Abstract Feasblty
More informationTitle Language Model for Information Retrieval
Ttle Language Model for Informaton Retreval Rong Jn Language Technologes Insttute School of Computer Scence Carnege Mellon Unversty Alex G. Hauptmann Computer Scence Department School of Computer Scence
More informationRecurrence. 1 Definitions and main statements
Recurrence 1 Defntons and man statements Let X n, n = 0, 1, 2,... be a MC wth the state space S = (1, 2,...), transton probabltes p j = P {X n+1 = j X n = }, and the transton matrx P = (p j ),j S def.
More informationA DYNAMIC CRASHING METHOD FOR PROJECT MANAGEMENT USING SIMULATION-BASED OPTIMIZATION. Michael E. Kuhl Radhamés A. Tolentino-Peña
Proceedngs of the 2008 Wnter Smulaton Conference S. J. Mason, R. R. Hll, L. Mönch, O. Rose, T. Jefferson, J. W. Fowler eds. A DYNAMIC CRASHING METHOD FOR PROJECT MANAGEMENT USING SIMULATION-BASED OPTIMIZATION
More informationGender Classification for Real-Time Audience Analysis System
Gender Classfcaton for Real-Tme Audence Analyss System Vladmr Khryashchev, Lev Shmaglt, Andrey Shemyakov, Anton Lebedev Yaroslavl State Unversty Yaroslavl, Russa vhr@yandex.ru, shmaglt_lev@yahoo.com, andrey.shemakov@gmal.com,
More informationBrigid Mullany, Ph.D University of North Carolina, Charlotte
Evaluaton And Comparson Of The Dfferent Standards Used To Defne The Postonal Accuracy And Repeatablty Of Numercally Controlled Machnng Center Axes Brgd Mullany, Ph.D Unversty of North Carolna, Charlotte
More informationOptimized ready mixed concrete truck scheduling for uncertain factors using bee algorithm
Songklanakarn J. Sc. Technol. 37 (2), 221-230, Mar.-Apr. 2015 http://www.sst.psu.ac.th Orgnal Artcle Optmzed ready mxed concrete truck schedulng for uncertan factors usng bee algorthm Nuntana Mayteekreangkra
More informationStock volatility forecasting using Swarm optimized Hybrid Network
Web Ste: www.jettcs.org Emal: edtor@jettcs.org, edtorjettcs@gmal.com Volume 2, Issue 3, May June 23 ISSN 2278-686 Stock volatlty forecastng usng Swarm optmzed Hybrd Network Puspanjal Mohapatra, Soumya
More informationRSA Cryptography using Designed Processor and MicroBlaze Soft Processor in FPGAs
RSA Cryptography usng Desgne Processor an McroBlaze Soft Processor n FPGAs M. Nazrul Islam Monal Dept. of CSE, Rajshah Unversty of Engneerng an Technology, Rajshah-6204, Banglaesh M. Al Mamun Dept. of
More informationLogical Development Of Vogel s Approximation Method (LD-VAM): An Approach To Find Basic Feasible Solution Of Transportation Problem
INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME, ISSUE, FEBRUARY ISSN 77-866 Logcal Development Of Vogel s Approxmaton Method (LD- An Approach To Fnd Basc Feasble Soluton Of Transportaton
More informationPOLYSA: A Polynomial Algorithm for Non-binary Constraint Satisfaction Problems with and
POLYSA: A Polynomal Algorthm for Non-bnary Constrant Satsfacton Problems wth and Mguel A. Saldo, Federco Barber Dpto. Sstemas Informátcos y Computacón Unversdad Poltécnca de Valenca, Camno de Vera s/n
More information