Solving bi-level linear programming problem through hybrid of immune genetic algorithm and particle swarm optimization algorithm

R.J. Kuo, Y.H. Lee, Ferani E. Zulvia and F.C. Tien

Applied Mathematics and Computation, 2015, vol. 266, issue C, 1013-1026

Abstract: Bi-level linear programming, consisting of upper level and lower level objectives, is a technique for modeling decentralized decision. This study presents a hybrid of immune genetic algorithm and vector-controlled particle swarm optimization (IGVPSO) to solve the bi-level linear programming problem (BLPP). It is applied to a supply chain model that is a BLPP. Using four problems from the literature and the supply chain distribution models, the computational results indicate that the proposed method is superior to some algorithms.

Keywords: Bi-level linear programming problem; Immune genetic algorithm; Particle swarm optimization; Supply chain management (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:266:y:2015:i:c:p:1013-1026

DOI: 10.1016/j.amc.2015.06.025

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