Aggregate Production Planning with Fuzzy Demand and Penalty Costs

Nepal H. Elkasrawy, Noha M. Galal, Ahmed F. Abdelmoneim
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引用次数: 2

Abstract

Uncertainty due to imprecise data and linguistically expressed information is inherent to real-life problems. Tactical production planning cannot neglect the presence of uncertainty due to the length of the planning horizon and the multitude of interacting factors affecting the manufacturing environment. Quantities expressed linguistically are best described by fuzzy sets to capture vagueness and to facilitate decision making in an uncertain context. This work considers developing an aggregate production plan with fuzzy demand and fuzzy cost elements. A fuzzy linear programming model is proposed that aims to minimize the total production costs and penalty costs caused by the unutilized capacity and unsatisfied demand. The proposed model is illustrated via a numerical example reflecting different cases that may occur in industry. The obtained results determine the optimum aggregate production plan while giving the decision-maker the flexibility to select the degree of satisfaction of constraints.
具有模糊需求和惩罚成本的总体生产计划
由于不精确的数据和语言表达信息而产生的不确定性是现实生活问题所固有的。战术生产计划不能忽视不确定性的存在,因为计划范围的长度和影响制造环境的众多相互作用的因素。语言上表达的数量最好用模糊集来描述,以捕捉模糊性,并促进在不确定环境下的决策。本文研究了一种具有模糊需求和模糊成本因素的综合生产计划。提出了一种模糊线性规划模型,以最小化生产总成本和因未利用产能和未满足需求而引起的惩罚成本为目标。通过一个反映工业中可能发生的不同情况的数值例子来说明所提出的模型。所得结果确定了最优的总生产计划,同时给予了决策者选择约束条件满足程度的灵活性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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