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A multi-objective supply chain configuration model for new products

机译:新产品的多目标供应链配置模型

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Configuring a supply chain for new products involves selecting how to source each stage in the supply chain given several alternatives that vary in cost, lead time, and other measures. One must also determine the best overall strategy for deploying safety stocks across the supply chain so as to buffer against demand uncertainty. Traditionally, this has been done based on costs (inventory cost, procurement cost, or a combination of both). This article introduces the use of a multi-objective optimisation model in configuring the supply chain during product development. In addition to using various production and inventory costs, the model makes use of subjective criteria such as alignment of business practices and financial objectives of member companies in configuring the supply chain. Fuzzy logic is used to analyse the subjective or qualitative variables, such as alignment of business cultures and practices. A genetic algorithm is used to solve the optimisation model. A bulldozer case study is then presented to benchmark and demonstrate the benefits of the proposed methodology.
机译:为新产品配置供应链涉及到在成本,交货时间和其他措施各不相同的几种选择下,选择如何在供应链的各个阶段采购资源。还必须确定在整个供应链中部署安全库存的最佳总体策略,以缓冲需求的不确定性。传统上,这是基于成本(库存成本,采购成本或两者的组合)完成的。本文介绍了在产品开发过程中多目标优化模型在配置供应链中的使用。除了使用各种生产和库存成本之外,该模型还利用主观标准,例如在配置供应链时调整成员公司的业务实践和财务目标。模糊逻辑用于分析主观或定性变量,例如业务文化和实践的一致性。遗传算法用于求解优化模型。然后介绍了一个推土机案例研究,以进行基准测试并证明了所提出方法的优势。

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