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Zbl 1221.90064
Kuo, R.J.; Han, Y.S.
A hybrid of genetic algorithm and particle swarm optimization for solving bi-level linear programming problem -- a case study on supply chain model. (English)
[J] Appl. Math. Modelling 35, No. 8, 3905-3917 (2011). ISSN 0307-904X

Summary: The main goal of supply chain management is to coordinate and collaborate the supply chain partners seamlessly. On the other hand, bi-level linear programming is a technique for modeling decentralized decision. It consists of the upper level and lower level objectives. Thus, this paper intends to apply bi-level linear programming to supply chain distribution problem and develop an efficient method based on hybrid of genetic algorithm (GA) and particle swarm optimization (PSO). The performance of the proposed method is ascertained by comparing the results with GA and PSO using four problems in the literature and a supply chain distribution model.

MSC 2000:: *90B90 Case-oriented studies in OR
90B06 Transportation, logistics
90C59 Approximation methods and heuristics

Keywords: bi-level linear programming; supply chain management; genetic algorithm; particle swarm optimization

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