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Multi-warehouse partial backlogging inventory system with inflation for non-instantaneous deteriorating multi-item under imprecise environment

机译:多仓库部分积压库存系统,用于不精确环境下的非瞬时恶化多项目的通货膨胀

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In this study, we explored a multi-item inventory model for non-instantaneous deteriorating items under inflation in fuzzy rough environment with multiple warehouse facilities, where one is an owned warehouse and others are rented warehouses with limited storage capacity. Due to a number of uncertainties in the environment, the various expenditures and coefficients are considered as a fuzzy rough type. The objective and constraints in fuzzy rough are made deterministic using Tr-Pos chance constrained technique. The demand of items is considered as stock dependent, and deterioration of items is assumed to be constant over time. The model allows shortages in owned warehouse subject to partial backlogging. The purpose of this study is to find the retailer's optimal replenishment policies to maximize the total profit. To illustrate the proposed model and also test the validity of the same, a numerical example is solved using the Mathematica-8.0 software. Sensitivity analysis is also performed to study the impact of important parameters on system decision variables, and its implications are discussed.
机译:在这项研究中,我们探讨了一种多项目库存模型,用于在模糊粗糙环境下的膨胀下的非瞬时恶化项目,其中包括多个仓库设施,其中一个是拥有的仓库,其他人是仓库,存储容量有限。由于环境中存在许多不确定性,各种支出和系数被认为是模糊粗糙类型。使用TR-POS机会约束技术进行模糊粗糙的目标和约束。物品的需求被认为是依赖性的,并且假设物品的恶化随着时间的推移是恒定的。该模型允许拥有的仓库内的短缺,但部分正负。本研究的目的是找到零售商的最佳补充政策,以最大限度地提高总利润。为了说明所提出的模型并还测试相同的有效性,使用Mathematica-8.0软件解决了数值示例。还进行了敏感性分析,以研究重要参数对系统决策变量的影响,并讨论其含义。

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