CEoptim: Cross-Entropy R Package for Optimization

Tim Benham, Qibin Duan, Dirk P. Kroese and Benoît Liquet

Journal of Statistical Software, 2017, vol. 076, issue i08

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.

Date: 2017-02-20
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Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:076:i08

DOI: 10.18637/jss.v076.i08

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