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Differential Evolution with DEoptim: An application to non-convex portfolio optimization
The R package DEoptim implements the differential evolution algorithm. This algorithm is an evolutionary technique similar to genetic algorithms that is useful for the solution of global optimization problems. In this note we provide an introduction to the package and demonstrate its utility for financial applications by solving a non-convex optimization problem.
DEoptim: An R package for global optimization by Differential Evolution
This article describes the R package DEoptim, which implements the Differential Evolution algorithm for global optimization of a real-valued function of a real-valued parameter vector. The implementation of Differential Evolution in DEoptim interfaces with C code for efficiency. The utility of the package is illustrated by case studies in fitting a Parratt model for X-ray reflectometry data and a Markov-Switching Generalized AutoRegressive Conditional Heteroskedasticity model for the returns of the Swiss Market Index.