메뉴 건너뛰기




Volumn 90, Issue 10, 2014, Pages 1146-1157

Simulation optimization using genetic algorithms with optimal computing budget allocation

Author keywords

genetic algorithms; optimal computing budget allocation; Ranking and selection; simulation; stochastic optimization

Indexed keywords

EFFICIENCY; GENETIC ALGORITHMS; GLOBAL OPTIMIZATION; ITERATIVE METHODS;

EID: 84910101323     PISSN: 00375497     EISSN: 17413133     Source Type: Journal    
DOI: 10.1177/0037549714548095     Document Type: Article
Times cited : (22)

References (42)
  • 1
    • 0000016172 scopus 로고
    • A Stochastic approximation method
    • Robbins H, Monro S. A Stochastic approximation method. Ann Math Stat. 1951 ; 22: 400-407
    • (1951) Ann Math Stat , vol.22 , pp. 400-407
    • Robbins, H.1    Monro, S.2
  • 2
    • 0001079593 scopus 로고
    • Stochastic estimation of the maximum of a regression function
    • Kiefer J, Wolfowitz J. Stochastic estimation of the maximum of a regression function. Ann Math Stat. 1952 ; 23: 462-466
    • (1952) Ann Math Stat , vol.23 , pp. 462-466
    • Kiefer, J.1    Wolfowitz, J.2
  • 3
    • 0026839090 scopus 로고
    • Multivariate stochastic approximation using a simultaneous perturbation gradient approximation
    • Spall JC. Multivariate stochastic approximation using a simultaneous perturbation gradient approximation. IEEE Trans Autom Control. 1992 ; 37: 332-341
    • (1992) IEEE Trans Autom Control , vol.37 , pp. 332-341
    • Spall, J.C.1
  • 5
    • 0030205012 scopus 로고    scopus 로고
    • Analysis of sample-path optimization
    • Robinson SM. Analysis of sample-path optimization. Math Oper Res. 1996 ; 21: 513-528
    • (1996) Math Oper Res , vol.21 , pp. 513-528
    • Robinson, S.M.1
  • 6
    • 0026938382 scopus 로고
    • Simulation optimization using simulated annealing
    • Haddock J, Mittenhall J. Simulation optimization using simulated annealing. Comput Ind Eng. 1992 ; 22: 387-395
    • (1992) Comput Ind Eng , vol.22 , pp. 387-395
    • Haddock, J.1    Mittenhall, J.2
  • 7
    • 0004215426 scopus 로고    scopus 로고
    • Norwell: Kluwer Academic Publishers
    • Glover F, Laguna M Tabu search. Norwell: Kluwer Academic Publishers ; 1997 :
    • (1997) Tabu Search
    • Glover, F.1    Laguna, M.2
  • 9
    • 0031356305 scopus 로고    scopus 로고
    • An integrated framework for deterministic and stochastic optimization
    • Shi L, Ólafsson S. An integrated framework for deterministic and stochastic optimization. ACM Proc Winter Simul Conf. 1997 ;: 358-365
    • (1997) ACM Proc Winter Simul Conf , pp. 358-365
    • Shi, L.1    Ólafsson, S.2
  • 10
    • 33644525898 scopus 로고    scopus 로고
    • Discrete optimization via simulation using COMPASS
    • Hong LJ, Nelson BL. Discrete optimization via simulation using COMPASS. Oper Res. 2006 ; 54: 115-129
    • (2006) Oper Res , vol.54 , pp. 115-129
    • Hong, L.J.1    Nelson, B.L.2
  • 11
    • 84877964064 scopus 로고    scopus 로고
    • An adaptive hyperbox algorithm for discrete optimization via simulation
    • Xu J, Nelson BL, Hong LJ. An adaptive hyperbox algorithm for discrete optimization via simulation. INFORMS J Comput. 2013 ; 25: 133-146
    • (2013) INFORMS J Comput , vol.25 , pp. 133-146
    • Xu, J.1    Nelson, B.L.2    Hong, L.J.3
  • 15
    • 0031223521 scopus 로고    scopus 로고
    • Genetic algorithms with a robust solution searching scheme
    • Tsutsui S, Ghosh A. Genetic algorithms with a robust solution searching scheme. IEEE Trans Evol Comput. 1997 ; 1: 201-208
    • (1997) IEEE Trans Evol Comput , vol.1 , pp. 201-208
    • Tsutsui, S.1    Ghosh, A.2
  • 16
    • 0000250677 scopus 로고
    • Genetic algorithms in noisy environments
    • Fitzpatrick M, Greffenstette JJ. Genetic algorithms in noisy environments. Mach Learn. 1988 ; 3: 101-120
    • (1988) Mach Learn , vol.3 , pp. 101-120
    • Fitzpatrick, M.1    Greffenstette, J.J.2
  • 17
    • 84878607496 scopus 로고    scopus 로고
    • Creating robust solutions by means of evolutionary algorithms
    • Branke J. Creating robust solutions by means of evolutionary algorithms. Lect Notes Comput Sci. 1998 ; 1498: 119-128
    • (1998) Lect Notes Comput Sci , vol.1498 , pp. 119-128
    • Branke, J.1
  • 18
    • 33745783272 scopus 로고    scopus 로고
    • Integrating techniques from statistical ranking into evolutionary algorithms
    • Schmidt C, Branke J, Chick SE. Integrating techniques from statistical ranking into evolutionary algorithms. Lect Notes Comput Sci. 2006 ; 3907: 752-763
    • (2006) Lect Notes Comput Sci , vol.3907 , pp. 752-763
    • Schmidt, C.1    Branke, J.2    Chick, S.E.3
  • 21
    • 76849089103 scopus 로고    scopus 로고
    • Industrial strength COMPASS: A comprehensive algorithm and software for optimization via simulation
    • Xu J, Nelson BL, Hong LJ. Industrial strength COMPASS: a comprehensive algorithm and software for optimization via simulation. ACM Trans Model Comput Simul. 2010 ; 20 (1). 3.1-3.29
    • (2010) ACM Trans Model Comput Simul , vol.20 , Issue.1 , pp. 31-329
    • Xu, J.1    Nelson, B.L.2    Hong, L.J.3
  • 22
    • 61349118110 scopus 로고    scopus 로고
    • Efficient simulation budget allocation for selecting an optimal subset
    • Chen CH, He D, Fu M, et al. Efficient simulation budget allocation for selecting an optimal subset. INFORMS J Comput. 2008 ; 20: 579-595
    • (2008) INFORMS J Comput , vol.20 , pp. 579-595
    • Chen, C.H.1    He, D.2    Fu, M.3
  • 23
    • 84904087613 scopus 로고    scopus 로고
    • Efficient simulation budget allocation for ranking the top m designs
    • Xiao H, Lee LH. Efficient simulation budget allocation for ranking the top m designs. Discrete Dyn Nat Soc. 2014 ;: 195054
    • (2014) Discrete Dyn Nat Soc , pp. 195054
    • Xiao, H.1    Lee, L.H.2
  • 24
    • 0030212017 scopus 로고    scopus 로고
    • A lower bound for the correct subset-selection probability and its application to discrete event system simulations
    • Chen CH. A lower bound for the correct subset-selection probability and its application to discrete event system simulations. IEEE Trans Autom Control. 1996 ; 41: 1227-1231
    • (1996) IEEE Trans Autom Control , vol.41 , pp. 1227-1231
    • Chen, C.H.1
  • 25
    • 0034225544 scopus 로고    scopus 로고
    • Simulation budget allocation for further enhancing the efficiency of ordinal optimization
    • Chen CH, Lin J, Yücesan E, et al. Simulation budget allocation for further enhancing the efficiency of ordinal optimization. Discrete Event Dyn Syst Theory Appl. 2000 ; 10: 251-270
    • (2000) Discrete Event Dyn Syst Theory Appl , vol.10 , pp. 251-270
    • Chen, C.H.1    Lin, J.2    Yücesan, E.3
  • 27
    • 0035460965 scopus 로고    scopus 로고
    • New two-stage and sequential procedures for selecting the best simulated system
    • Chick S, Inoue K. New two-stage and sequential procedures for selecting the best simulated system. Oper Res. 2001 ; 49: 1609-1624
    • (2001) Oper Res , vol.49 , pp. 1609-1624
    • Chick, S.1    Inoue, K.2
  • 28
    • 0035435933 scopus 로고    scopus 로고
    • Inoue. New procedures to select the best simulated system using common random numbers
    • Chick S, Inoue K. Inoue. New procedures to select the best simulated system using common random numbers. Manage Sci. 2001 ; 47: 1133-1149
    • (2001) Manage Sci , vol.47 , pp. 1133-1149
    • Chick, S.1    Inoue, K.2
  • 29
    • 84927701190 scopus 로고    scopus 로고
    • Efficient computing budget allocation for finding simplest good design
    • Jia QS, Zhou E, Chen CH. Efficient computing budget allocation for finding simplest good design. IIE Trans. 2013 ; 45: 736-750
    • (2013) IIE Trans , vol.45 , pp. 736-750
    • Jia, Q.S.1    Zhou, E.2    Chen, C.H.3
  • 30
    • 84863466908 scopus 로고    scopus 로고
    • Efficient selection of a set of good enough designs with complexity preference
    • Yan S, Zhou E, Chen CH. Efficient selection of a set of good enough designs with complexity preference. IEEE Trans Autom Sci Eng. 2012 ; 9: 596-606
    • (2012) IEEE Trans Autom Sci Eng , vol.9 , pp. 596-606
    • Yan, S.1    Zhou, E.2    Chen, C.H.3
  • 31
    • 84859741915 scopus 로고    scopus 로고
    • Efficient computing budget allocation for simulation-based policy improvement
    • Jia QS. Efficient computing budget allocation for simulation-based policy improvement. IEEE Trans Autom Sci Eng. 2012 ; 9: 342-352
    • (2012) IEEE Trans Autom Sci Eng , vol.9 , pp. 342-352
    • Jia, Q.S.1
  • 32
    • 84872082903 scopus 로고    scopus 로고
    • Simulation-based policy improvement for energy management in commercial office buildings
    • Jia QS, Shen J, Xu Z, et al. Simulation-based policy improvement for energy management in commercial office buildings. IEEE Trans Smart Grid. 2012 ; 3: 2211-2223
    • (2012) IEEE Trans Smart Grid , vol.3 , pp. 2211-2223
    • Jia, Q.S.1    Shen, J.2    Xu, Z.3
  • 33
    • 17744368519 scopus 로고    scopus 로고
    • Optimal computing budget allocation for multi-objective simulation models
    • Lee LH, Chew EP, Teng S, et al. Optimal computing budget allocation for multi-objective simulation models. ACM Proc Winter Simul Conf. 2004 ;: 586-594
    • (2004) ACM Proc Winter Simul Conf , pp. 586-594
    • Lee, L.H.1    Chew, E.P.2    Teng, S.3
  • 34
    • 77953626786 scopus 로고    scopus 로고
    • Finding the non-dominated Pareto set for multi-objective simulation models
    • Lee LH, Chew EP, Teng S, et al. Finding the non-dominated Pareto set for multi-objective simulation models. IIE Trans. 2010 ; 42: 656-674
    • (2010) IIE Trans , vol.42 , pp. 656-674
    • Lee, L.H.1    Chew, E.P.2    Teng, S.3
  • 35
    • 84898786826 scopus 로고    scopus 로고
    • Optimal computing budget allocation for complete ranking
    • Xiao H, Lee LH, Ng KM. Optimal computing budget allocation for complete ranking. IEEE Trans Autom Sci Eng. 2014 ; 11: 516-524
    • (2014) IEEE Trans Autom Sci Eng , vol.11 , pp. 516-524
    • Xiao, H.1    Lee, L.H.2    Ng, K.M.3
  • 36
    • 84869158518 scopus 로고    scopus 로고
    • Approximate simulation budget allocation for selecting the best design in the presence of stochastic constraints
    • Lee LH, Pujowidianto NA, Li LW, et al. Approximate simulation budget allocation for selecting the best design in the presence of stochastic constraints. IEEE Trans Autom Control. 2012 ; 57: 2940-2945
    • (2012) IEEE Trans Autom Control , vol.57 , pp. 2940-2945
    • Lee, L.H.1    Pujowidianto, N.A.2    Li, L.W.3
  • 37
    • 84881142237 scopus 로고    scopus 로고
    • Optimal sampling laws for stochastically constrained simulation optimization on finite sets
    • Hunter SR, Pasupathy R. Optimal sampling laws for stochastically constrained simulation optimization on finite sets. INFORMS J Comput. 2013 ; 25: 527-542
    • (2013) INFORMS J Comput , vol.25 , pp. 527-542
    • Hunter, S.R.1    Pasupathy, R.2
  • 38
    • 84863243909 scopus 로고    scopus 로고
    • Simulation optimization using the particle swarm optimization with optimal computing budget allocation
    • Zhang S, Chen P, Lee LH, et al. Simulation optimization using the particle swarm optimization with optimal computing budget allocation. ACM Proc Winter Simul Conf. 2011 ;: 4303-4314
    • (2011) ACM Proc Winter Simul Conf , pp. 4303-4314
    • Zhang, S.1    Chen, P.2    Lee, L.H.3
  • 39
    • 76849090697 scopus 로고    scopus 로고
    • Simulation optimization using the cross-entropy method with optimal computing budget allocation
    • He D, Lee LH, Chen CH, et al. Simulation optimization using the cross-entropy method with optimal computing budget allocation. ACM Trans Model Comput Simul. 2010 ; 20 (1). 4
    • (2010) ACM Trans Model Comput Simul , vol.20 , Issue.1 , pp. 4
    • He, D.1    Lee, L.H.2    Chen, C.H.3
  • 42
    • 17744392866 scopus 로고    scopus 로고
    • A large deviations perspective on ordinal optimization
    • Glynn P, Juneja S. A large deviations perspective on ordinal optimization. ACM Proc Winter Simul Conf. 2004 ;: 577-585
    • (2004) ACM Proc Winter Simul Conf , pp. 577-585
    • Glynn, P.1    Juneja, S.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.