The cross-entropy method for combinatorial and continuous optimization
type: Item
instance of: scholarly article
title: The cross-entropy method for combinatorial and continuous optimization
zbMATH Open document ID: 0941.65061
DOI: 10.1023/A:1010091220143
published in: Methodology and Computing in Applied Probability
publication date: 2000-08-07T00:00:00Z
review text: A new and fast method, called the cross-entropy method, for finding an optimal solution of problems of the form: \[ \min_x L(x),\quad x\in X\in\mathbb{R}^n, \] where \(X\) is a convex bounded domain, \(L(x)\) is a bounded nonconvex function defined on \(X\). It is also allowed that either \(L(x)\) or \(X\) or both have a discrete (combinatorial) structure. The author presents a fast randomized adaptive algorithm for solving this problem in the sense that the algorithm converges with very high probability to a very small neighborhood of an optimal solution. Numerical tests for both continuous and combinatorial optimization problems are given.
Mathematics Subject Classification ID: 65K05
Mathematics Subject Classification ID: 94A17
Mathematics Subject Classification ID: 90C26
Mathematics Subject Classification ID: 90C27
zbMATH DE Number: 1394698
zbMATH Keywords: combinatorial continuous optimization
zbMATH Keywords: numerical tests
zbMATH Keywords: cross-entropy method
zbMATH Keywords: fast randomized adaptive algorithm
author: Reuven Y. Rubinstein
reviewed by: Hans Benker
describes a project that uses: Global Optimization Toolbox For Maple
MaRDI profile type: Publication
full work available at URL: a:1010091220143
OpenAlex ID: W1577352482
description: scientific article; zbMATH DE number 1394698