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An efficient tabu search algorithm for the distributed permutation flowshop scheduling problem
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DOI：10.1080/00207543.2011.644819.png)
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Distributed permutation flow shop scheduling problem (DPFSP) is a newly proposed scheduling problem, which is a generalisation of classical permutation flowshop scheduling problem. Studies on algorithms for solving this problem are in the early stage. In this paper, we propose a new tabu algorithm for solving this problem, which exploits a novel tabu strategy. A method that swaps sub-sequences of jobs is presented to generate neighbourhood. Moreover, an enhanced local search method is proposed and also combined into the tabu algorithm. We also use the well-known benchmark of Taillard (extended to the distributed permutation flowshop problems) to test the algorithm. From the intensive experiments we carried out, we conclude that the proposed tabu algorithm outperforms all the existing algorithms including heuristics algorithms (i.e. NEH1, NEH2, VND(a) and VND(b)) and a hybrid genetic algorithm, so the best-known solutions for 472 instances are updated. Moreover, it is worth mentioning that the efficiency of the tabu algorithm is also better than that of the genetic algorithm.
Keyword:
tabu search
distributed scheduling
flowshop
sequence swapping
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Tabu search for total tardiness minimization in flowshop scheduling problems禁忌搜索flowshop调度问题中的总迟到最小化
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