Solving tri-level programming problems using a particle swarm optimization algorithm

Han, J; Zhang, G; Hu, Y; Lu, J

Solving tri-level programming problems using a particle swarm optimization algorithm

Han, J Zhang, G

Hu, Y Lu, J

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Publication Type:: Conference Proceeding
Citation:: Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015, 2015, pp. 569 - 574
Issue Date:: 2015-11-20

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Field	Value	Language
dc.contributor.author	Han, J	en_US
dc.contributor.author	Zhang, G https://orcid.org/0000-0003-3960-0583	en_US
dc.contributor.author	Hu, Y	en_US
dc.contributor.author	Lu, J https://orcid.org/0000-0003-0690-4732	en_US
dc.date.issued	2015-11-20	en_US
dc.identifier.citation	Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015, 2015, pp. 569 - 574	en_US
dc.identifier.isbn	9781467373173	en_US
dc.identifier.uri	http://hdl.handle.net/10453/41400
dc.description.abstract	© 2015 IEEE. Tri-level programming, a special case of multilevel programming, arises to deal with decentralized decision-making problems that feature interacting decision entities distributed throughout three hierarchical levels. As tri-level programming problems are strongly NP-hard and the existing solution approaches lack universality in solving such problems, the purpose of this study is to propose an intelligence-based heuristic algorithm to solve tri-level programming problems involving linear and nonlinear versions. In this paper, we first propose a general tri-level programming problem and discuss related theoretical properties. A particle swarm optimization (PSO) algorithm is then developed to solve the tri-level programming problem. Lastly, a numerical example is adopted to illustrate the effectiveness of the proposed PSO algorithm.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP0557154
dc.relation	http://purl.org/au-research/grants/arc/DP140101366
dc.relation.ispartof	Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015	en_US
dc.relation.isbasedon	10.1109/ICIEA.2015.7334176	en_US
dc.title	Solving tri-level programming problems using a particle swarm optimization algorithm	en_US
dc.type	Conference Proceeding
utslib.for	080105 Expert Systems	en_US
utslib.for	080605 Decision Support and Group Support Systems	en_US
utslib.for	080108 Neural, Evolutionary and Fuzzy Computation	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US

Abstract:

© 2015 IEEE. Tri-level programming, a special case of multilevel programming, arises to deal with decentralized decision-making problems that feature interacting decision entities distributed throughout three hierarchical levels. As tri-level programming problems are strongly NP-hard and the existing solution approaches lack universality in solving such problems, the purpose of this study is to propose an intelligence-based heuristic algorithm to solve tri-level programming problems involving linear and nonlinear versions. In this paper, we first propose a general tri-level programming problem and discuss related theoretical properties. A particle swarm optimization (PSO) algorithm is then developed to solve the tri-level programming problem. Lastly, a numerical example is adopted to illustrate the effectiveness of the proposed PSO algorithm.

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