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
fDate :
6/21/1905 12:00:00 AM
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;
Conference_Titel :
Simulation Conference Proceedings, 1999 Winter
Conference_Location :
Phoenix, AZ
Print_ISBN :
0-7803-5780-9
DOI :
10.1109/WSC.1999.823113
