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A two-level GA to solve an integrated multi-item supplier selection model

机译:两级遗传算法解决集成的多项目供应商选择模型

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In this paper, we investigate an integrated multi-item supplier selection model. The mathematical model which is a nonlinear binary programming is derived. To the best of our knowledge, it is the first study in the literature that considers both integration and multi-item nature of supplier selection process. In addition, proposed model allows the buyer to select multiple suppliers. In the proposed model, inventory costs for both supplier/suppliers and buyer, production costs for supplier/suppliers, and transportation costs are considered where supplier/suppliers use EPQ model and the buyer uses EOQ model to control the inventories. To solve the proposed SCM model, based on genetic algorithm, a novel Two-Level heuristic algorithm is developed. The results show that the proposed algorithm works properly in the term of both CPU time and the quality of solutions. Finally, using numerical examples, some useful managerial analysis are presented. These analysis provide valuable insights into the problem that can help the supply chain managers.
机译:在本文中,我们研究了集成的多项目供应商选择模型。推导了作为非线性二进制规划的数学模型。据我们所知,这是文献中首次考虑供应商选择过程的整合和多项目性质的研究。此外,建议的模型允许买方选择多个供应商。在建议的模型中,在供应商/供应商使用EPQ模型而买方使用EOQ模型控制库存的情况下,要考虑供应商/供应商和买方的库存成本,供应商/供应商的生产成本以及运输成本。为了解决提出的SCM模型,基于遗传算法,提出了一种新颖的两级启发式算法。结果表明,该算法在CPU时间和解决方案质量两方面均能正常工作。最后,使用数值示例,提出了一些有用的管理分析。这些分析提供了对问题的宝贵见解,可以帮助供应链经理。

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