Title: A novel particle swarm algorithm for multi-objective optimisation problem

Authors: Jiande Zhang; Chenrong Huang; Jinbao Xu; Jingui Lu

Addresses: Department of Computer Engineering, Nanjing Institute of Technology, Nanjing 211167, Jiangsu Province, China ' Department of Computer Engineering, Nanjing Institute of Technology, Nanjing 211167, Jiangsu Province, China ' Department of Computer Engineering, Nanjing Institute of Technology, Nanjing 211167, Jiangsu Province, China ' Department of Mechanical and Power Engineering, Nanjing University of Technology, Nanjing 210009, Jiangsu Province, China

Abstract: To maintain the diversity and convergence of Pareto optimal solutions for multi-objective problem, an improved particle swarm optimisation algorithm based on dynamical changed inertia weight is proposed to improve algorithm's ability of exploitation and exploration. By this method, if a particle finds a better solution then more energy is given onto the current velocity to speed up exploitation, and vice versa. The computer simulations for three well-known benchmark functions taken from the multi-objective optimisation literature are used to evaluate the performance of the proposed approach. Numerical experiments have been performed to evaluate the efficiency of the algorithm.

Keywords: multi-objective optimisation; particle swarm optimisation; PSO; dynamic inertia weight; adaptive parameter; simulation.

DOI: 10.1504/IJMIC.2013.053544

International Journal of Modelling, Identification and Control, 2013 Vol.18 No.4, pp.380 - 386

Published online: 29 Apr 2013 *

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