An Improved Artificial Bee Colony for Solving Multi-Objective Optimization Problems

Artificial bee colony (ABC) algorithm is a novel optimizer which simulates bees' foraging behavior in solution space for finding global optimal solution with reasonable criteria. In this paper, an improved artificial bee colony is proposed to solve multi-objective (MO) problems. In order to guide bees toward to Pareto optimal solutions, bees' moving behavior is modified to make ABC capable for solving multi-objective problems. In order to test the proposed method, five IEEE CEC 2009 test functions and performance metric are adopted. Besides, three MO optimizers are taken into comparison.