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首页> 外文期刊>International journal of industrial and systems engineering >A robust possibilistic programming model for simultaneous decision of inventory lot-size, supplier selection and transportation mode selection
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A robust possibilistic programming model for simultaneous decision of inventory lot-size, supplier selection and transportation mode selection

机译:一个健壮的可能编程模型,可同时决定库存批量,供应商选择和运输方式选择

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摘要

As a result of the uncertain changes in global currencies, exchange rates have become a critical part of suppliers' selection problem. In the present paper the problem of supplier, transportation mode selection and inventory replenishment decision (STSI) in the presence of uncertain changes of currency exchange rates and price discounts have been studied. The present article addresses the STSI problem for a buyer sourcing a product from heterogeneous suppliers. Global suppliers' selection procedure is based on the prices that suppliers offer in their local currencies. Late deliveries and rejections also exert influence on sourcing and inventory replenishment decisions. The proposed model is a bi-objective mathematical programming, objective functions of which are minimising the total cost and the late delivery of items. In order to cope with uncertain parameters effectively, a robust possibilistic programming approach is utilised. Finally, to assess the robustness of the solutions obtained by the novel robust optimisation model, our model's results are compared to those generated by the chance-constrained programming model under the data of STAM SANAT Company. Further, the advantages of using this integrated approach versus a sequential approach under currency fluctuations are shown.
机译:由于全球货币的不确定性,汇率已成为供应商选择问题的关键部分。本文研究了在汇率和价格折扣不确定的情况下的供应商,运输方式选择和库存补给决策(STSI)问题。本文解决了STSI问题,即买方从异构供应商处采购产品。全球供应商的选择程序基于供应商以当地货币提供的价格。延迟交货和拒绝也会对采购和库存补充决策产生影响。所提出的模型是一个双目标数学规划,其目标功能是使总成本和项目的延迟交付最小化。为了有效地应对不确定的参数,使用了鲁棒的可能编程方法。最后,为了评估由新型鲁棒优化模型获得的解决方案的鲁棒性,将我们的模型结果与机会约束编程模型在STAM SANAT Company的数据下生成的结果进行比较。此外,还显示了在汇率波动的情况下使用此集成方法相对于顺序方法的优势。

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