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Stochastic flexible flow shop scheduling problem under quantitative and qualitative decision criteria

机译:定量和定性决策准则下的随机柔性流水车间调度问题

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This paper addresses a bi-criteria stochastic flexible flow shop (SFFS) scheduling problem in which one criterion is quantitative and the other is qualitative. The quantitative criterion is the total weighted tardiness and the qualitative criterion is the importance of the customer for the company. To solve this problem, the integral analysis method (IAM), which consists of four stages (description of the problem, cardinal analysis, ordinal analysis and integration analysis), was used. The cardinal analysis implements both a mixed integral linear programming (MILP) model and a simulation-optimization approach for the total weighted tardiness solution. The ordinal analysis is performed by stochastic multicriteria acceptability analysis with ordinal data (SMAA-O) in which each alternative is qualified depending on customer importance. Finally, to address the integral analysis, deterministic SMAA is applied to select those alternatives that exhibited the best integral characteristics in terms of minimizing tardiness penalty costs and timely fulfillment of due dates according to customer strategic importance for the company. Results show that IAM enables selection of the alternatives that accomplish in the best way both types of criteria.
机译:本文提出了一种双准则随机柔性流水车间调度问题,其中一个准则是定量准则,另一准则是定性准则。定量标准是总加权迟滞,定性标准是客户对公司的重要性。为了解决此问题,使用了包括四个阶段(问题描述,基数分析,序数分析和积分分析)的积分分析方法(IAM)。基本分析同时实现了混合加权线性规划(MILP)模型和总加权拖尾率解决方案的仿真优化方法。序数分析是通过对序数数据(SMAA-O)进行的随机多准则可接受性分析来执行的,其中每种选择方案都取决于客户的重要性。最后,针对积分分析,确定性SMAA用于根据客户对公司的战略重要性,选择具有最佳积分特性的替代方案,以最大程度地减少延误罚款成本并及时履行到期日。结果表明,IAM可以选择以最佳方式完成两种标准的备选方案。

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