Novel Mutative Particle Swarm Optimization Algorithm for Discrete Optimization.
Ahmad Ihsan Mohd Yassin, Nooritawati Md Tahir, Mohd Khairul Mohd Salleh, Hasliza Abu Hassan, Azlee Zabidi, Husna Zainol Abidin · GEM · 2009
Mutative Particle Swarm Optimization (MPSO) is swarm-based stochastic optimization algorithm combined with the mutative function inspired by Genetic Algorithm (GA). The algorithm searches for the solution by combining swarming behavior, as well as mutation of the particles to accelerate the search process. This paper presents a modification to the MPSO algorithm for it to solve Integer Programming (IP) problems. The proposed approach was compared with the works of Parsopoulos & Vrahatis on the Seven Integer Programming (SIP) benchmark functions. The results show that the proposed method was able to outperform the performance in Parsopoulos & Vrahatis, with better convergence at a significantly faster rate.