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首页> 外文会议>International Conference on Service Systems and Service Management(ICSSSM'04) vol.2; 20040719-21; Beijing(CN) >Multiobjective Optimization on Facility Location and Inventory Deployment with Customer Service Consideration
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Multiobjective Optimization on Facility Location and Inventory Deployment with Customer Service Consideration

机译：考虑客户服务的设施位置和库存部署的多目标优化

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摘要

The decisions on facility location and inventory deployment have considerable impacts on a supply chain's profitability and effectiveness. The total cost of all supply chain activities is often used as the unique optimization criterion in the i literature. However, it is important to take customer service issues into account in current competitive environment. In this paper, we present a simulation-based multiobjective optimization method that makes decisions on facility location and multi-echelon inventory deployment. The proposed method comprises a multiobjective optimizer and a simulation module. The optimizer, based on a multiobjective genetic algorithm (MOGA), is used to direct the search for compromised solutions regarding to two conflicting criteria, i.e. costs and customer service level. Decision variables include the facility locations and inventory control policies. Candidate solutions suggested by the optimizer are evaluated subsequently by the discrete-event simulation module, developed in a flexible manner that enables automatic simulation of various supply chain structures without human intervention. The uniqueness of the proposed method is that it not only performs multiobjectiye optimization, but more importantly, it optimizes supply chain structure and addresses each configuration's operational performances through simulation. Stochastic facts along the whole supply chain are also taken into account during the optimization process. The method is applied to solve a case study from automotive industry. A set of Pareto-optimal solutions are obtained, which achieve various trade-offs between two criteria: costs and customer service level.
机译：设施位置和库存部署的决定对供应链的盈利能力和有效性产生重大影响。所有供应链活动的总成本在文献中经常被用作唯一的优化标准。但是，在当前竞争环境中考虑客户服务问题很重要。在本文中，我们提出了一种基于仿真的多目标优化方法，该方法可以对设施位置和多级库存部署做出决策。所提出的方法包括多目标优化器和仿真模块。基于多目标遗传算法（MOGA）的优化程序用于针对两个相冲突的标准（即成本和客户服务水平）针对受损的解决方案进行搜索。决策变量包括设施位置和库存控制策略。优化器建议的候选解决方案随后由离散事件模拟模块评估，该模块以灵活的方式开发，可以自动模拟各种供应链结构而无需人工干预。所提出的方法的独特性在于它不仅执行多目标优化，而且更重要的是，它优化了供应链结构并通过仿真解决了每个配置的操作性能。在优化过程中，还会考虑整个供应链中的随机事实。该方法用于解决汽车行业的案例研究。获得了一组帕累托最优解决方案，该解决方案在成本和客户服务水平这两个标准之间实现了各种折衷。

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