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A meta-heuristic approach supported by NSGA-II for the design and plan of supply chain networks considering new product development

机译:NSGA-II支持的考虑新产品开发的元启发式方法用于供应链网络的设计和计划

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There are many reasons for the growing interest in developing new product projects for any firm. The most embossed reason is surviving in a highly competitive industry which the customer tastes are changing rapidly. A well-managed supply chain network can provide the most profit for firms due to considering new product development. Along with profit, customer satisfaction and production of new products are goals which lead to a more efficient supply chain. As new products appear in the market, the old products could become obsolete, and then phased out. The most important parameter in a supply chain which considers new and developed products is the time that developed and new products are introduced and old products are phased out. With consideration of the factors noted above, this study proposes to design a tri-objective multi-echelon multi-product multi-period supply chain model, which incorporates product development and new product production and their effects on supply chain configuration. The supply chain under consideration is assumed to consist of suppliers, manufacturers, distributors and customer groups. In terms of overcoming NP-hardness of the proposed model and in order to solve the complicated problem, a non-dominated sorting genetic algorithm is employed. As there is no benchmark available in the literature, the non-dominated ranking genetic algorithm is developed to validate the results obtained and some test problems are provided to show the applicability of the proposed methodology and evaluate the performance of the algorithms.
机译:对于任何一家公司而言,开发新产品项目的兴趣日益浓厚的原因很多。最具压纹的原因是在竞争激烈的行业中幸存下来,客户的品味正在迅速变化。考虑到新产品的开发,一个管理良好的供应链网络可以为公司提供最大的利润。除了利润之外,客户满意度和新产品生产都是目标,它们可以导致更高效的供应链。随着新产品出现在市场中,旧产品可能会过时,然后逐步淘汰。在考虑新产品和新产品的供应链中,最重要的参数是开发和引入新产品以及淘汰旧产品的时间。考虑到上述因素,本研究建议设计一个三目标多级多产品多产品期的供应链模型,该模型将产品开发和新产品生产及其对供应链配置的影响纳入考虑。假定正在考虑的供应链包括供应商,制造商,分销商和客户群。在克服所提出模型的NP难点和解决复杂问题的基础上,采用了一种非支配排序遗传算法。由于文献中没有可用的基准,因此开发了非支配的排序遗传算法来验证所获得的结果,并提供了一些测试问题以证明所提出的方法的适用性并评估算法的性能。

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