An Improved Particle Swarm Optimization for Solving Bilevel Multiobjective Programming Problem

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 f...

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Published in:Journal of Applied Mathematics Vol. 2012; no. 2012; pp. 1441 - 1453-491
Main Authors: Guo, Xuning, Zheng, Yue, Hu, Tiesong, Zhang, Tao
Format: Journal Article
Language:English
Published: Cairo, Egypt Hindawi Limiteds 01.01.2012
Hindawi Publishing Corporation
John Wiley & Sons, Inc
Wiley
Subjects:
Algorithms
Approximation
Heuristic
Linear programming
Mathematical models
Optimization
Pareto optimality
Pareto optimum
Programming
Strategy
Studies
ISSN:1110-757X, 1687-0042
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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.
AbstractList 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.
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.
Author Guo, Xuning
Hu, Tiesong
Zheng, Yue
Zhang, Tao
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ContentType Journal Article
Copyright Copyright © 2012 Tao Zhang et al.
Copyright © 2012 Tao Zhang et al. 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.
Copyright 2012 Hindawi Publishing Corporation
Copyright_xml – notice: Copyright © 2012 Tao Zhang et al.
– notice: Copyright © 2012 Tao Zhang et al. 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.
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Snippet An improved particle swarm optimization (PSO) algorithm is proposed for solving bilevel multiobjective programming problem (BLMPP). For such problems, the...
An improved particle swarm optimization (PSO) algorithm is proposed for solving bilevel multiobjective programming problem (BLMPP). For such problems, the...
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StartPage 1441
SubjectTerms Algorithms
Approximation
Heuristic
Linear programming
Mathematical models
Optimization
Pareto optimality
Pareto optimum
Programming
Strategy
Studies
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Title An Improved Particle Swarm Optimization for Solving Bilevel Multiobjective Programming Problem
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