Particle Swarm Optimization Based on Smoothing Approach for Solving a Class of Bi-Level Multiobjective Programming Problem

As a metaheuristic, Particle Swarm Optimization (PSO) has been used to solve the Bi-level Multiobjective Programming Problem (BMPP). However, in the existing solving approach based on PSO for the BMPP, the upper level and the lower level problem are solved interactively by PSO. In this paper, we pre...

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Veröffentlicht in:Cybernetics and information technologies : CIT Jg. 17; H. 3; S. 59 - 74
Hauptverfasser: He, Qingping, Lv, Yibing
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Sofia Sciendo 01.09.2017
De Gruyter Brill Sp. z o.o., Paradigm Publishing Services
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ISSN:1314-4081, 1311-9702, 1314-4081
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Zusammenfassung:As a metaheuristic, Particle Swarm Optimization (PSO) has been used to solve the Bi-level Multiobjective Programming Problem (BMPP). However, in the existing solving approach based on PSO for the BMPP, the upper level and the lower level problem are solved interactively by PSO. In this paper, we present a different solving approach based on PSO for the BMPP. Firstly, we replace the lower level problem of the BMPP with Kuhn-Tucker optimality conditions and adopt the perturbed Fischer-Burmeister function to smooth the complementary conditions. After that, we adopt PSO approach to solve the smoothed multiobjective programming problem. Numerical results show that our solving approach can obtain the Pareto optimal front of the BMPP efficiently.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1314-4081
1311-9702
1314-4081
DOI:10.1515/cait-2017-0030