Computers & Operations Research ( IF 4.6 ) Pub Date : 2021-04-19 , DOI: 10.1016/j.cor.2021.105332 Mohamed Frihat , Atidel B.Hadj-Alouane , Chérif Sadfi
This paper deals with a real manufacturing scheduling problem that is particularly encountered in the tannery industries. This problem often integrates employee timetabling and production scheduling. The employee timetabling problem is addressed in the context of skill requirements and under availability and legislative constraints. The production scheduling is considered as a re-entrant hybrid job-shop problem with time lags and sequence dependent setup times, under machine availability constraints. The objective is to minimize the labor cost, while respecting a maximum makespan and a maximum tardiness constraints. Two different models and exact resolution methods are proposed, using Mixed Integer Linear Programming (MILP) and Constraint Programming (CP). Numerical experimentations are conducted to compare and evaluate their performances, based on randomly generated instances. The results show that the CP model is slower than the MILP model in terms of finding optimal solutions for large instances, but is more efficient in generating feasible solutions. Thus, providing a feasible initial solution to the MILP model using the CP model is a promising hybrid approach to reduce the computational time.
中文翻译:
员工时间表与车间调度集成问题的优化
本文涉及制革业中特别遇到的实际制造调度问题。此问题通常将员工时间表和生产计划集成在一起。员工时间表问题是在技能要求的背景下以及在可用性和法律约束下解决的。在机器可用性约束下,生产计划被认为是带有时滞和依赖于序列的设置时间的可重入混合作业车间问题。目的是在最大限度地延长工期和最大延误约束的同时,将劳动力成本降至最低。提出了两种不同的模型和精确的分辨率方法,分别使用混合整数线性规划(MILP)和约束规划(CP)。进行数值实验以比较和评估其性能,基于随机生成的实例。结果表明,就寻找最优解而言,CP模型要比MILP模型慢。 大型实例,但在生成可行解决方案方面效率更高。因此,使用CP模型为MILP模型提供可行的初始解决方案是减少计算时间的有前途的混合方法。