Simulation-based optimization using simulated annealing with ranking and selection

被引:43
作者
Ahmed, MA [1 ]
Alkhamis, TM [1 ]
机构
[1] Kuwait Univ, Dept Stat & Operat Res, Coll Sci, Safat, Kuwait
关键词
stochastic optimization; Markov chains; simulation; ranking and selection; simulated annealing;
D O I
10.1016/S0305-0548(00)00073-3
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In this paper, we present a new iterative method that combines the simulated annealing method and the ranking and selection procedures for solving discrete stochastic optimization problems. The number of visit to every state by the proposed algorithm is used to estimate the optimal solution. We show that the configuration that has been visited most often in the first m iterations converges almost surely to a globally optimum solution. We present empirical results that illustrate the performance of the proposed method.
引用
收藏
页码:387 / 402
页数:16
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