Abstract and Applied Analysis
Volume 2012 (2012), Article ID 102482, 20 pages
http://dx.doi.org/10.1155/2012/102482
Research Article

Solving Bilevel Multiobjective Programming Problem by Elite Quantum Behaved Particle Swarm Optimization

Tao Zhang,1,2 Tiesong Hu,1 Jia-wei Chen,3 Zhongping Wan,3 and Xuning Guo1

1State Key Laboratory of Water Resource and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
2School of Information and Mathematics, Yangtze University, Jingzhou 434023, China
3School of Mathematics and Statistics, Wuhan University, Wuhan 430072, China

Received 25 August 2012; Accepted 18 October 2012

Academic Editor: Xiaolong Qin

Copyright © 2012 Tao Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

An elite quantum behaved particle swarm optimization (EQPSO) algorithm is proposed, in which an elite strategy is exerted for the global best particle to prevent premature convergence of the swarm. The EQPSO algorithm is employed for solving bilevel multiobjective programming problem (BLMPP) in this study, which has never been reported in other literatures. Finally, we use eight different test problems to measure and evaluate the proposed algorithm, including low dimension and high dimension BLMPPs, as well as attempt to solve the BLMPPs whose theoretical Pareto optimal front is not known. The experimental results show that the proposed algorithm is a feasible and efficient method for solving BLMPPs.