A study of constraint-handling techniques in brain storm optimization

A study on three BSO algorithm versions: Brain Storm Optimization Algorithm (BSO), Modified Brain Storm Optimization Algorithm (MBSO) and Simple Modified Brain Storm Optimization Algorithm (SMBSO), for constrained numerical optimization problems is presented in this paper. The aim of the study is to know the performance of this recent Swarm Intelligence (SI) algorithm on constrained search spaces. The feasibility rules, ε-constrained method, and stochastic ranking are used as constraint-handling techniques. The performance of each version is analysed by solving 24 well-known benchmark problems. The final results suggest MBSO and the ε-constrained method as a good option to deal with constrained problems.