DocumentCode
1622911
Title
Iterative ranking-and-selection for large-scale optimization
Author
ólafsson, Sigurdur
Author_Institution
Dept. of Ind. & Manuf. Syst. Eng., Iowa State Univ., Ames, IA, USA
Volume
1
fYear
1999
fDate
6/21/1905 12:00:00 AM
Firstpage
479
Abstract
We develop a novel algorithm for simulation based optimization where the number of alternatives is finite but very large. Our approach draws on recent work in adaptive random search and from ranking-and-selection. In particular, it combines the nested partitions method for global optimization and Y. Rinott´s (1978) two-stage ranking-and-selection procedure. We prove asymptotic convergence of the new algorithm under fairly mild conditions
Keywords
adaptive systems; convergence; iterative methods; optimisation; random processes; search problems; simulation; adaptive random search; asymptotic convergence; global optimization; iterative ranking-and-selection; large-scale optimization; mild conditions; nested partitions method; simulation based optimization; two-stage ranking-and-selection procedure; Analytical models; Discrete event simulation; Large-scale systems; Manufacturing industries; Manufacturing systems; Modeling; Optimization methods; Partitioning algorithms; Stochastic systems; Systems engineering and theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Simulation Conference Proceedings, 1999 Winter
Conference_Location
Phoenix, AZ
Print_ISBN
0-7803-5780-9
Type
conf
DOI
10.1109/WSC.1999.823113
Filename
823113
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