Constrained artificial bee colony algorithm for optimization problems

Abstract

Artificial Bee Colony (ABC) algorithm is a well known swarm intelligence algorithms which have shown a competitive performance with respect to other population-based algorithms. However, this algorithm has poor exploitation ability. To address this issue, an Improved Constrained Artificial Bee Colony (icABC) algorithm is proposed where three new solution search equations are introduced respectively to employed bee, onlooker bee and scout bee phases. This algorithm is tested on several constrained benchmark Problems. The numerical results demonstrate that the icABC is competitive with other state-of-the-art constrained ABC algorithm under consideration.