An Improved Harmony Search Algorithm for Constrained Multi-Objective Optimization

An improved harmony search algorithm for constrained multi-objective optimization problems is proposed in this paper. Inspired by Particle Swarm Optimization, an inductor particle is introduced to speed up the convergence rate of the CMOHS. Two populations are adopted to increase the opportunity of finding the optimal solutions. Numerical experiments are divided into two parts: the first one compares the CMOHS with NSGA-II, and the other one compares the CMOHS with the algorithm without the inductor individual. The results show that the CMOHS is more effective than NSGA-II, and the induction mechanism improved the convergence and diversity of the algorithm.