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首页> 外文期刊>Journal of Optimization in Industrial Engineering >Solving a Multi-Item Supply Chain Network Problem by Three Meta-heuristic Algorithms
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Solving a Multi-Item Supply Chain Network Problem by Three Meta-heuristic Algorithms

机译：三个元启发式算法解决多项供应链网络问题

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The supply chain network design not only assists organizations production process (e.g.,plan, control and execute a product’s flow) but also ensure what is the growing need for companies in a longterm. This paper develops a three-echelon supply chain network problem including multiple plants, multiple distributors, and multiple retailers with amulti-mode demand satisfaction policy inside of production planning and maintenance. The problem is formulated as a mixed-integer linear programming model. Because of its NP-hardness, three meta-heuristic algorithms(i.e., tabu search, harmony search and genetic algorithm) are used to solve the given problem. Also, theTaguchi method is used to choose the best levels of the parameters of the proposedmeta-heuristic algorithms. The results show that HS has abetter solution quality than two other algorithms.
机译：供应链网络设计不仅有助于组织生产过程（例如，计划，控制和执行产品的流程），而且还要确保公司在长期内越来越多的需求。本文开发了三个梯队供应链网络问题，包括多个工厂，多个分销商和多个零售商，在生产规划和维护内部具有氨气模式需求满意度政策。该问题被配制为混合整数线性编程模型。由于其NP硬度，三个元启发式算法（即，禁忌搜索，和声搜索和遗传算法）用于解决给定的问题。此外，ThetAguchi方法用于选择Proposmometa-Heuristic算法的参数的最佳级别。结果表明，HS具有比另外两种算法的Addter解决方案质量。

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