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Column generation based decomposition algorithm for a parallel machine just-in-time scheduling problem

机译:并行机实时调度问题的基于列生成的分解算法

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We propose a column generation based exact decomposition algorithm for the problem of scheduling n jobs with an unrestrictively large common due date on m identical parallel machines to minimize total weighted earliness and tardiness. We first formulate the problem as an integer program, then reformulate it, using Dantzig-Wolfe decomposition, as a set partitioning problem with side constraints. Based on this set partitioning formulation, a branch and bound exact solution algorithm is developed for the problem. In the branch and bound tree, each node is the linear relaxation problem of a set partitioning problem with side constraints. This linear relaxation problem is solved by column generation approach where columns represent partial schedules on single machines and are generated by solving two single machine subproblems. Our computational results show that this decomposition algorithm is capable of solving problems with up to 60 jobs in reasonable cpu time.
机译:我们提出了一种基于列生成的精确分解算法,用于在m台相同的并行计算机上调度具有不受限制的大到期日的n个作业的问题,以最大程度地减少总加权提前期和拖延时间。我们首先将问题表述为整数程序,然后使用Dantzig-Wolfe分解将其重新表述为带有边约束的集合划分问题。基于该集合划分公式,针对该问题开发了分支定界精确解算法。在分支定界树中,每个节点都是具有侧约束的集合划分问题的线性松弛问题。此线性松弛问题通过列生成方法解决,其中列表示单台机器上的部分计划,并通过解决两个单台机器子问题来生成。我们的计算结果表明,这种分解算法能够在合理的CPU时间内解决多达60个作业的问题。

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