论文信息 - On the Convergence of the Cross-Entropy Method

On the Convergence of the Cross-Entropy Method

The cross-entropy method is a relatively new method for combinatorial optimization. The idea of this method came from the simulation field and then was successfully applied to different combinatorial optimization problems. The method consists of an iterative stochastic procedure that makes use of the importance sampling technique. In this paper we prove the asymptotical convergence of some modifications of the cross-entropy method.

L. Margolin | L. Margolin

[1] Alastair J. Walker,et al. An Efficient Method for Generating Discrete Random Variables with General Distributions , 1977, TOMS.

[2] Reuven Y. Rubinstein,et al. Optimization of computer simulation models with rare events , 1997 .

[3] R. Rubinstein. The Cross-Entropy Method for Combinatorial and Continuous Optimization , 1999 .

[4] R. Rubinstein. Combinatorial Optimization, Cross-Entropy, Ants and Rare Events , 2001 .

[5] Walter J. Gutjahr,et al. ACO algorithms with guaranteed convergence to the optimal solution , 2002, Inf. Process. Lett..

[6] Reuven Y. Rubinstein,et al. Cross-entropy and rare events for maximal cut and partition problems , 2002, TOMC.

[7] Dirk P. Kroese,et al. Combinatorial Optimization via Cross-Entropy , 2004 .

[8] Dirk P. Kroese,et al. The Cross-Entropy Method , 2011, Information Science and Statistics.