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A deteriorating multi-item inventory model with fuzzy costs and resources based on two different defuzzification techniques

机译:基于两种不同的去模糊化技术的具有模糊成本和资源的恶化多项目库存模型

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Normally inventory models of deteriorating items, such as food products, vegetables, etc. involve imprecise parameters, like imprecise inventory costs, fuzzy storage area, fuzzy budget allocation, etc. In this paper, we aim to provide two defuzzification techniques for two fuzzy inventory models using (ⅰ) extension principle and duality theory of non-linear programming and (ⅱ) interval arithmetic. On the basis of Zadeh's extension principle, two non-linear programs parameterized by the possibility level a are formulated to calculate the lower and upper bounds of the minimum average cost at a-level, through which the membership function of the objective function is constructed. In interval arithmetic technique the interval objective function has been transformed into an equivalent deterministic multi-objective problem defined by the left and right limits of the interval. This formulation corresponds to the possibility level, α = 0.5. Finally, the multi-objective problem is solved by a multi-objective genetic algorithm (MOGA). The model has been illustrated through a numerical example and solved for different values of possibility level, α through extension principle and for α = 0.5 via MOGA. As a particular case, the results have been obtained for the inventory model without deterioration. Results from two methods for α = 0.5 are compared.
机译:通常,诸如食品,蔬菜等恶化项目的库存模型涉及不精确的参数,例如不精确的库存成本,模糊的存储区域,模糊的预算分配等。本文旨在为两种模糊的库存提供两种去模糊化技术使用(ⅰ)扩展原理和非线性对偶理论和(theory)区间算术的模型。根据Zadeh的可拓原理,制定了两个由可能性级别a进行参数化的非线性程序,以计算最小平均成本在a级别的上下限,从而构造目标函数的隶属函数。在区间算术技术中,区间目标函数已转换为由区间的左右边界定义的等效确定性多目标问题。该公式对应于可能性水平,α= 0.5。最后,通过多目标遗传算法(MOGA)解决了多目标问题。该模型已通过数值示例进行了说明,并针对不同的可能性级别值,通过扩展原理的α以及通过MOGA的α= 0.5进行了求解。在特定情况下,已经获得了库存模型的结果而没有恶化。比较了两种方法在α= 0.5时的结果。

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