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A Disruption Recovery Model in a Production-Inventory System with Demand Uncertainty and Process Reliability

机译:具有需求不确定性和过程可靠性的生产库存系统中的中断恢复模型

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This paper develops a risk management tool for a production-inventory system that involves an imperfect production process and faces production disruption and demand uncertainty. In this paper, the demand uncertainty is represented as fuzzy variable and the imperfectness is expressed as process reliability. To deal with the production scheduling in this environment, a non-linear constrained optimization model has been formulated with an objective of maximizing the graded mean integration value (GMIV) of the total expected profit. The model is applied to solve the production-inventory problem with single as well as multiple disruptions on a real time basis that basically revises the production quantity in each cycle in the recovery time window. We propose a genetic algorithm (GA) based heuristic to solve the model and obtain an optimal recovery plan. A numerical example is presented to explain usefulness of the developed model.
机译:本文为涉及生产过程不完善,面临生产中断和需求不确定性的生产库存系统开发了一种风险管理工具。本文将需求不确定性表示为模糊变量,将不完善性表示为过程可靠性。为了处理这种环境下的生产计划,已制定了一个非线性约束优化模型,其目的是使总预期利润的分级平均积分值(GMIV)最大化。该模型用于实时解决一次或多次中断的生产库存问题,该问题基本上可以在恢复时间窗口内修改每个循环中的生产量。我们提出了一种基于遗传算法的启发式算法来求解模型并获得最佳的恢复计划。给出了一个数值示例来说明开发模型的有用性。

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