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A two-stage stochastic programming model for production lot-sizing and scheduling under demand and raw material quality uncertainties

机译:需求和原材料质量不确定性下的生产批量计划和调度的两阶段随机规划模型

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摘要

Production planning and scheduling focus on efficient use of resources and are widely used in the manufacturing industry, especially when the system operates in an uncertain environment. The goal of this paper is to provide a two-stage stochastic programming framework for a multi-period, multi-product, lot-sizing and scheduling problem considering uncertainties in both demand and the quality of raw materials. The objectives are to determine the number of units to be produced and the production sequence so that the total production costs are minimised. The decisions made in the first stage include the basic production plan along with the production quantities and sequences, which are later updated with recourse decisions on overtime production made in the second-stage. To demonstrate the proposed decision-making framework, a case study for a manufacturing facility producing braking equipment for the automotive industry was conducted. The results show that the stochastic model is more effective in production planning under the uncertainties considered. The managerial insights derived from this study will facilitate the decision making for determining optimal production quantities and sequences under uncertainties.
机译:生产计划和调度着重于资源的有效利用,并且在制造业中被广泛使用,尤其是当系统在不确定的环境中运行时。本文的目的是为考虑到需求和原材料质量的不确定性的多周期,多产品,批量确定和调度问题提供一个两阶段随机编程框架。目的是确定要生产的单元数量和生产顺序,以使总生产成本降至最低。在第一阶段做出的决定包括基本的生产计划以及生产数量和顺序,随后通过在第二阶段做出的关于加班生产的追索权决定进行更新。为了演示建议的决策框架,对生产汽车行业制动设备的制造工厂进行了案例研究。结果表明,在考虑不确定因素的情况下,随机模型在生产计划中更为有效。从这项研究中得出的管理见解将有助于在不确定性下确定最佳生产数量和顺序的决策。

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