Solving bilevel multiobjective programming problem by elite quantum behaved particle swarm optimization
type: Item
instance of: scholarly article
title: Solving bilevel multiobjective programming problem by elite quantum behaved particle swarm optimization
zbMATH Open document ID: 1256.68139
DOI: 10.1155/2012/102482
author: Tao Zhang
author: Tiesong Hu
author: Xuning Guo
author: Jiawei Chen
author: Zhongping Wan
published in: Abstract and Applied Analysis
publication date: 2013-02-04T00:00:00Z
review text: Summary: 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.
Mathematics Subject Classification ID: 68T20
Mathematics Subject Classification ID: 81P68
Mathematics Subject Classification ID: 90C29
zbMATH DE Number: 6134014
Wikidata QID: Q58694817
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2012/102482
OpenAlex ID: W2130796165
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description: scientific article; zbMATH DE number 6134014