Journal of Applied Mathematics

An Improved Particle Swarm Optimization for Solving Bilevel Multiobjective Programming Problem

Tao Zhang, Tiesong Hu, Yue Zheng, and Xuning Guo

Full-text: Open access

Abstract

An improved particle swarm optimization (PSO) algorithm is proposed for solving bilevel multiobjective programming problem (BLMPP). For such problems, the proposed algorithm directly simulates the decision process of bilevel programming, which is different from most traditional algorithms designed for specific versions or based on specific assumptions. The BLMPP is transformed to solve multiobjective optimization problems in the upper level and the lower level interactively by an improved PSO. And a set of approximate Pareto optimal solutions for BLMPP is obtained using the elite strategy. This interactive procedure is repeated until the accurate Pareto optimal solutions of the original problem are found. Finally, some numerical examples are given to illustrate the feasibility of the proposed algorithm.

Article information

Source
J. Appl. Math., Volume 2012 (2012), Article ID 626717, 13 pages.

Dates
First available in Project Euclid: 14 December 2012

Permanent link to this document
https://projecteuclid.org/euclid.jam/1355495105

Digital Object Identifier
doi:10.1155/2012/626717

Mathematical Reviews number (MathSciNet)
MR2910912

Zentralblatt MATH identifier
1244.90251

Citation

Zhang, Tao; Hu, Tiesong; Zheng, Yue; Guo, Xuning. An Improved Particle Swarm Optimization for Solving Bilevel Multiobjective Programming Problem. J. Appl. Math. 2012 (2012), Article ID 626717, 13 pages. doi:10.1155/2012/626717. https://projecteuclid.org/euclid.jam/1355495105


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