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CONSTRAINED INTEGRATED INVENTORY MODEL FOR MULTI-ITEM UNDER MIXTURE OF DISTRIBUTIONS

机译:分布混合约束的多项目约束集成库存模型

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When the demand of different customers are not identical during the lead time, then one cannot use only a single distribution to describe the demand during that lead time. Hence, in this paper we have studied a mixture of normal distributions and a mixture of distribution free for several products under vendor-buyer integrated approach (coordination between both parties). Many integrated inventory models have proved that the integrated total cost is minimum when compared to sum of the total cost of the individuals. The inventory is continuously reviewed by the buyer and next order is placed when the inventory reaches some level called reorder level. The buyer has limited warehouse space capacity and also limited budget to purchase all products. The lead time of receiving all products from the vendor is a variable which is controlled by adding crashing cost. Shortages are allowed for all products and a fraction of shortages will be backordered and the remaining are lost. A mathematical model is developed and a solution procedure is employed in this study to obtain optimum order quantities, lead time and number of shipments in which the integrated total cost function attains its minimum subject to the floor space constraint and budget constraint. The expected integrated cost function is non-linear mixed integer with inequality constraints. Therefore, the proposed model have been solved by using Lagrangian multiplier technique. Finally numerical examples and sensitivity analysis were performed to illustrate the effectiveness of the proposed model.
机译:如果在交付周期内不同客户的需求不相同,则不能仅使用一个分布来描述在交付周期内的需求。因此,在本文中,我们研究了在卖方-买方集成方法下(双方之间的协调)几种产品的正态分布混合和自由分布的混合。许多综合库存模型已证明,与个人总成本之和相比,综合总成本最低。买方不断审查库存,当库存达到某种水平(称为“重新订购”水平)时,下一个订单。买方的仓库空间容量有限,购买所有产品的预算也有限。从供应商处接收所有产品的提前期是一个变量,可以通过增加崩溃成本来控制。所有产品都允许出现短缺,部分短缺将被补货,其余的将丢失。建立了数学模型,并在本研究中采用了求解程序来获得最佳订单数量,提前期和发货数量,其中综合总成本函数在满足占地面积和预算约束的情况下达到其最小值。预期的综合成本函数是具有不等式约束的非线性混合整数。因此,所提出的模型已经通过使用拉格朗日乘数技术得以解决。最后通过数值算例和敏感性分析来说明所提模型的有效性。

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