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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Vydáno v:Cybernetics and information technologies : CIT Ročník 17; číslo 3; s. 59 - 74
Hlavní autoři: He, Qingping, Lv, Yibing
Médium: Journal Article
Jazyk:angličtina
Vydáno: Sofia Sciendo 01.09.2017
De Gruyter Brill Sp. z o.o., Paradigm Publishing Services
Témata:
Bi-level multiobjective programming problem
optimality conditions
particle swarm optimization
scalarization method
smoothing method
ISSN:1314-4081, 1311-9702, 1314-4081
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Shrnutí: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.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:1314-4081
1311-9702
1314-4081
DOI:10.1515/cait-2017-0030