Journal
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
Volume 208, Issue 1, Pages 19-27Publisher
ELSEVIER
DOI: 10.1016/j.ejor.2010.09.002
Keywords
Continuous optimization; Simulation; Indifference Zone; Probabilistic search; Golden Region; Metamodeling
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Simulation Optimization (SO) is a class of mathematical optimization techniques in which the objective function can only be numerically evaluated through simulation. In this paper, a new SO approach called Golden Region (GR) search is developed for continuous problems. GR divides the feasible region into a number of (sub) regions and selects one region in each iteration for further search based on the quality and distribution of simulated points in the feasible region and the result of scanning the response surface through a metamodel. Monte Carlo experiments show that the GR method is efficient compared to three well-established approaches in the literature. We also prove the asymptotic convergence in probability to a global optimum for a large class of random search methods in general and GR in particular. (C) 2010 Elsevier B.V. All rights reserved.
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