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The Shifting Bottleneck Procedure for Job Shop Scheduling

  • Joseph Adams

    (Graduate School of Industrial Administration, Carnegie-Mellon University, Pittsburgh, Pennsylvania 15213)

  • Egon Balas

    (Graduate School of Industrial Administration, Carnegie-Mellon University, Pittsburgh, Pennsylvania 15213)

  • Daniel Zawack

    (American Airlines)

Registered author(s):

    We describe an approximation method for solving the minimum makespan problem of job shop scheduling. It sequences the machines one by one, successively, taking each time the machine identified as a bottleneck among the machines not yet sequenced. Every time after a new machine is sequenced, all previously established sequences are locally reoptimized. Both the bottleneck identification and the local reoptimization procedures are based on repeatedly solving certain one-machine scheduling problems. Besides this straight version of the Shifting Bottleneck Procedure, we have also implemented a version that applies the procedure to the nodes of a partial search tree. Computational testing shows that our approach yields consistently better results than other procedures discussed in the literature. A high point of our computational testing occurred when the enumerative version of the Shifting Bottleneck Procedure found in a little over five minutes an optimal schedule to a notorious ten machines/ten jobs problem on which many algorithms have been run for hours without finding an optimal solution.

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    File URL: http://dx.doi.org/10.1287/mnsc.34.3.391
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    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 34 (1988)
    Issue (Month): 3 (March)
    Pages: 391-401

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    Handle: RePEc:inm:ormnsc:v:34:y:1988:i:3:p:391-401
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