標題: Ordinal optimization approach to stochastic simulation optimization problems and applications
作者: Lin, Shin-Yeu
Horng, Shih-Cheng
電控工程研究所
Institute of Electrical and Control Engineering
關鍵字: ordinal optimization;stochastic simulation optimization;neural network;genetic algorithm;polling system;average waiting time
公開日期: 2006
摘要: In this paper, we propose an ordinal optimization approach to solve for a good enough solution of the stochastic simulation optimization problem with huge decision-variable space. We apply the proposed ordinal optimization algorithm to G/G/1/K polling systems to solve for a good enough number-limited service discipline to minimize the weighting average waiting time. We have compared our results with those obtained by the existing service disciplines and found that our approach outperforms the existing ones. We have also used the genetic algorithm and simulated annealing method to solve the same stochastic simulation optimization problem, and the results show that our approach is much more superior in the aspects of computational efficiency and the quality of obtained solution.
URI: http://hdl.handle.net/11536/17388
ISBN: 0-88986-559-0
期刊: Proceedings of the 15th IASTED International Conference on Applied Simulation and Modelling
起始頁: 274
結束頁: 279
Appears in Collections:Conferences Paper