CEoptim: Cross-Entropy R Package for Optimization

TL;DR

CEoptim is an R package that implements the cross-entropy optimization method, a versatile technique applicable to various optimization problems including continuous, discrete, and constrained scenarios.

Contribution

This paper introduces CEoptim, an R package that provides an accessible implementation of the cross-entropy optimization method for diverse problem types.

Findings

Effective in model fitting tasks

Successfully applied to combinatorial optimization

Demonstrates robustness in maximum likelihood estimation

Abstract

The cross-entropy (CE) method is 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.