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Efficient mixed integer programming models for family scheduling problems

机译:用于家庭计划问题的高效混合整数规划模型

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This paper proposes several mixed integer programming models which incorporate optimal sequence properties into the models, to solve single machine family scheduling problems. The objectives are total weighted completion time and maximum lateness, respectively. Experiment results indicate that there are remarkable improvements in computational efficiency when optimal sequence properties are included in the models. For the total weighted completion time problems, the best model solves all of the problems up to 30-jobs within 5 s, all 50-job problems within 4 min and about 1/3 of the 75-job to 100-job problems within 1 h. For maximum lateness problems, the best model solves almost all the problems up to 30-jobs within 11 min and around half of the 50-job to 100-job problems within 1 h.
机译:本文提出了几种混合整数规划模型,这些模型将最优序列属性纳入模型中,以解决单机族调度问题。目标分别是总加权完成时间和最大延迟。实验结果表明,当模型中包含最佳序列属性时,计算效率将得到显着提高。对于总加权完成时间问题,最佳模型可在5 s内解决所有问题,包括最多30个工作,在4分钟内解决所有50个工作问题,以及在1个问题内解决75个工作到100个工作问题的大约1/3 H。对于最大的迟到问题,最佳模型可以在11分钟内解决几乎所有问题,最多30个工作,在1小时内解决50个问题至100个问题的一半。

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