Modified artificial bee colony algorithm for constrained problems optimization

Abstract

 Abstract—Original Karaboga's artificial bee colony (ABC) algorithm was applicable to unconstrained problems only and modifications for constrained problems were introduced later. In this article we propose an improved artificial bee colony algorithm for constrained problems. Since the ABC algorithm for constrained problems does not consider the initial population to be feasible we introduced a modification, besides penalty function and Deb's rule, in a form of ―smart bee‖ (SB) which uses its historical memories for the location and quality of food sources. This modified SB-ABC algorithm was tested on standard benchmark functions for constrained optimization problems and proved to be better. Keywords—Artificial bee colony, Constrained optimization, Nature inspired metaheuristic algorithms, Swarm intelligence.