Generalized Simulated Annealing for Global Optimization: The GenSA Package

Many problems in statistics, finance, biology, pharmacology, physics, mathematics, economics, and chemistry involve determination of the global minimum of multidimensional functions.R packages for different stochastic methods such as genetic algorithms and differential evolution have been developed and successfully used in the R community.Based on Tsallis statistics, the R package GenSA was developed for generalized simulated annealing to process complicated non-linear objective functions with a large number of local minima.In this paper we provide a brief introduction to the R package and demonstrate its utility by solving a non-convex portfolio optimization problem in finance and the Thomson problem in physics.GenSA is useful and can serve as a complementary tool to, rather than a replacement for, other widely used R packages for optimization.