Multi-objective Bird Swarm Algorithm

Abstract

Most real-world optimization problems involve multiple objectives and parameters. In this paper, bird swarm algorithm (BSA) is modified with non-dominated sorting approach and parallel coordinates. A developed algorithm, known as multi-objective BSA (MOBSA) is proposed. When the external archive for non-dominated solutions is full to overflowing, the solution with greatest density would be rejected. The approaches were tested and compared on benchmark problems. Based on these results, the MOBSA has access to better convergence and spread of Pareto front.