CEoptim: cross-entropy R package for optimization

Benham, Tim, Duan, Qibin, Kroese, Dirk P. and Liquet, Benoît (2017) CEoptim: cross-entropy R package for optimization. Journal of Statistical Software, 76 1: 1-29. doi:10.18637/jss.v076.i08

Author Benham, Tim
Duan, Qibin
Kroese, Dirk P.
Liquet, Benoît
Title CEoptim: cross-entropy R package for optimization
Journal name Journal of Statistical Software   Check publisher's open access policy
ISSN 1548-7660
Publication date 2017-02-01
Sub-type Article (original research)
DOI 10.18637/jss.v076.i08
Open Access Status DOI
Volume 76
Issue 1
Start page 1
End page 29
Total pages 29
Place of publication Alexandria, VA, United States
Publisher American Statistical Association
Language eng
Abstract The cross-entropy (CE) method is a simple and versatile technique for optimization, based on Kullback-Leibler (or cross-entropy) minimization. The method can be applied to a wide range of optimization tasks, including continuous, discrete, mixed and constrained optimization problems. The new package CEoptim provides the R implementation of the CE method for optimization. We describe the general CE methodology for optimization and well as some useful modifications. The usage and efficacy of CEoptim is demonstrated through a variety of optimization examples, including model fitting, combinatorial optimization, and maximum likelihood estimation.
Keyword Constrained optimization
Continuous optimization
Discrete optimization
Kullback-Leibler divergence
Maximum likelihood
R Regression
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Mathematics and Physics
HERDC Pre-Audit
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 1 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 1 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Tue, 11 Apr 2017, 00:25:16 EST by Web Cron on behalf of Learning and Research Services (UQ Library)