Simulation optimization using the cross-entropy method with optimal computing budget allocation

Donghai He, Loo Hay Lee, Chun-Hung Chen, Michael C. Fu, Segev Wasserkrug
2010 ACM Transactions on Modeling and Computer Simulation  
We propose to improve the efficiency of simulation optimization by integrating the notion of optimal computing budget allocation into the Cross-Entropy (CE) method, which is a global optimization search approach that iteratively updates a parameterized distribution from which candidate solutions are generated. This article focuses on continuous optimization problems. In the stochastic simulation setting where replications are expensive but noise in the objective function estimate could mislead
more » ... he search process, the allocation of simulation replications can make a significant difference in the performance of such global optimization search algorithms. A new allocation scheme D. He et al. is developed based on the notion of optimal computing budget allocation. The proposed approach improves the updating of the sampling distribution by carrying out this computing budget allocation in an efficient manner, by minimizing the expected mean-squared error of the CE weight function. Numerical experiments indicate that the computational efficiency of the CE method can be substantially improved if the ideas of computing budget allocation are applied. ACM Reference Format: He, D., Lee, L. H., Chen, C.-H., Fu, M. C., and Wasserkrug, S. 2010. Simulation optimization using the cross-entropy method with optimal computing budget allocation. ACM Trans. Model. Comput.
doi:10.1145/1667072.1667076 fatcat:ankwlionrbhkxfrow6k3ql6rim