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A tabu-search heuristic for the flexible-resource flow shop scheduling problem

  • Applications In Production And Scheduling
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Abstract

This paper presents a tabu-search heuristic for the flexible-resource flow shop scheduling (FRFS) problem [7]. The FRFS problem generalizes the classic flow shop scheduling problem by allowing job-operation processing times to depend on the amount of resource assigned to an operation; the objective is to determine simultaneously the job sequence, resource-allocation policy, and operation start times that optimize system performance. The tabu-search heuristic (TSH) employs a nested-search strategy based on a decomposition of the FRFS problem into these three components. We discuss computational experience with the THS procedure on more than 1600 test problems. The results show that TSH is effective in obtaining near-optimal solutions to the FRFS test problems. In particular, TSH generates optimal solutions for more than 70% of the test problems for which optimal solutions are known; overall, these solutions are within 0.3% of optimality on the average, and within 2.5% of optimality in the worst case.

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Authors and Affiliations

  1. Fuqua School of Business, Duke University, 27706, Durham, NC, USA

    Richard L. Daniels & Joseph B. Mazzola

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  1. Richard L. Daniels
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  2. Joseph B. Mazzola
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Additional information

This research was supported in part by National Science Foundation grant SES90-22940.

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Daniels, R.L., Mazzola, J.B. A tabu-search heuristic for the flexible-resource flow shop scheduling problem. Ann Oper Res 41, 207–230 (1993). https://doi.org/10.1007/BF02023075

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