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A hybrid of genetic algorithm and particle swarm optimization for solving bi-level linear programming problem - A case study on supply chain model

机译:遗传算法与粒子群算法的混合求解双层线性规划问题-以供应链模型为例

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摘要

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.
机译:供应链管理的主要目标是无缝地协调和协作供应链合作伙伴。另一方面,双层线性规划是一种用于建模分散决策的技术。它由上层和下层目标组成。因此,本文打算将双层线性规划应用于供应链分配问题,并开发一种基于遗传算法和粒子群优化算法混​​合的有效方法。通过使用文献中的四个问题和供应链分配模型,将结果与GA和PSO进行比较,可以确定所提出方法的性能。

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