The Cross-Entropy Method for Continuous Multi-Extremal Optimization

The Cross-Entropy Method for Continuous Multi-extremal Optimization

In recent years, the cross-entropy method has been successfully applied to a wide range of discrete optimization tasks. In this paper we consider the cross-entropy method in the context of continuous optimization. We demonstrate the effectiveness of the cross-entropy method for solving difficult continuous multi-extremal optimization problems, including those with nonlinear constraints.

The Cross-Entropy Method for Combinatorial and Continuous Optimization

The Cross-Entropy Method for Optimization

The cross-entropy method is a versatile heuristic tool for solving difficult estimation and optimization problems, based on Kullback–Leibler (or cross-entropy) minimization. As an optimization method it unifies many existing populationbased optimization heuristics. In this chapter we show how the cross-entropy method can be applied to a diverse range of combinatorial, continuous, and noisy opti...

A cross entropy algorithm for continuous covering location problem

Covering problem tries to locate the least number of facilities and each demand has at least one facility located within a specific distance.This paper considers a cross entropy algorithm for solving the mixed integer nonlinear programming (MINLP) for covering location model.The model is solved to determine the best covering value.Also, this paper proposes aCross Entropy (CE) algorithm consider...

Convergence properties of the cross-entropy method for discrete optimization

We present new theoretical convergence results on the Cross-Entropy method for discrete optimization. Our primary contribution is to show that a popular implementation of the Cross-Entropy method converges, and finds an optimal solution with probability arbitrarily close to 1. We also give necessary conditions and sufficient conditions under which an optimal solution is generated eventually wit...