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Different behaviour of a double branch-and-bound algorithm on Fm | prmu | C_(max) and Fm | block | C_(max) problems

机译:Fm上的双分支定界算法的不同行为prmu | C_(max)和Fm |块| C_(max)问题

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In this paper we face the permutation flow-shop scheduling problem with a makespan objective function in two variants, with and without storage space between machines. We use an improved branch and bound algorithm, suitable for parallel computation, to solve these problems, and auxiliary heuristics to attain an initial good solution. The auxiliary heuristics proposed are built by two steps: in the first step a permutation is obtained; in the second step a local search procedure is applied. The improvement obtained by the local search procedure on NEH heuristic as first step is shown. Since the flow-shop scheduling problem with storage space is a relaxation of the problem without storage space, some elements and procedures developed for that problem can be used in both problems. In particular, some bounding procedures, for instance Nabeshima or Lageweg bounding schema, can be adapted. Moreover, the reversibility property holds on both problems. Consequently a double branch and bound algorithm can be appfied simultaneously to the direct and the inverse instances. The same sets of data are submitted to heuristics and to the double branch-and-bound algorithm, LOMPEN, assuming first they are instances of flow-shop scheduling problem with storage space and later they are instances of flow-shop scheduling problem without storage space. The algorithms are coded in a similar way; therefore the behaviour and performance can be compared.
机译:在本文中,我们面对带有两个目标变量的makepan目标函数的置换流水车间调度问题,机器之间有存储空间,也有没有存储空间。我们使用一种适用于并行计算的改进的分支定界算法来解决这些问题,并使用辅助启发式方法来获得初始的良好解决方案。提出的辅助启发式方法分为两个步骤:第一步,获得置换;第二步,获得置换。在第二步中,将应用本地搜索过程。第一步显示了通过本地搜索过程获得的NEH启发式改进。由于具有存储空间的流水车间调度问题是没有存储空间的问题的缓解,因此针对该问题开发的某些元素和过程可以在两个问题中使用。特别地,可以适应某些边界过程,例如Nabeshima或Lageweg边界模式。而且,可逆性在两个问题上都成立。因此,可以将双分支定界算法同时应用于正例和逆例。将相同的数据集提交给启发式方法和双分支定界算法LOMPEN,首先假设它们是具有存储空间的流水车间调度问题的实例,然后是没有存储空间的流水车间调度问题的实例。算法的编码方式类似。因此可以比较行为和性能。

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