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A variable block insertion heuristic for permutation flowshops with makespan criterion

机译：具有MakEspan标准的可变块插入启发式置换流程

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摘要

This paper proposes a populated variable block insertion heuristic (PVBIH) algorithm for solving the permutation flowshop scheduling problem with the makespan criterion. The PVBIH algorithm starts with a minimum block size being equal to one. It removes a block from the current solution and inserts it into the partial solution randomly with a predetermined move size. A local search is applied to the solution found after several block moves. If the new solution generated after the local search is better than the current solution, it replaces the current solution. It retains the same block size as long as it improves. Otherwise, the block size is incremented by one and a simulated annealing-type of acceptance criterion is used to accept the new solution. This process is repeated until the block size reaches at the maximum block size. In addition, we present a randomized profile fitting heuristic with excellent results. Extensive computational results on the Taillard's well-known benchmark suite show that the proposed PVBIH algorithm substantially outperforms the differential evolution algorithm (NS-SGDE) recently proposed in the literature.
机译：本文提出了一种填充的可变块插入启发式（PVBIH）算法，用于解决MakeSpan标准的置换流程调度问题。 PVBIH算法从最小块大小开始等于1。它从电流溶液中移除块，并随机将其插入部分溶液中，以预定的移动尺寸随机地插入部分溶液中。在多个块移动后的解决方案中应用本地搜索。如果在本地搜索后生成的新解决方案优于当前解决方案，则替换当前解决方案。它保持相同的块大小，只要它改进即可。否则，块大小由一个递增，并且使用模拟退火类型的验收标准来接受新解决方案。重复此过程，直到块大小达到最大块大小。此外，我们介绍了一个随机型材拟合启发式，具有出色的结果。淘册知名基准套件上的广泛计算结果表明，所提出的PVBIH算法在文献中最近提出的差分演进算法（NS-SGDE）显着优于差异。

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