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A priority list based heuristic for the job shop problem

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  • P M E Shutler

    (Nanyang Technological University)

Abstract

A priority list for the job shop scheduling problem is defined to be any permutation of a set of symbols where the symbol for each job appears as many times as the number of its operations. Every priority list can be associated in a natural way with a feasible schedule, and every feasible schedule arises in this way. Priority lists are therefore a representation of feasible schedules that avoid the problems normally associated with schedule infeasibility. As a result, the three ingredients of local search heuristics, namely picking initial starting schedules, constructing search neighbourhoods and computing makespans, become faster and easier when performed in the space of priority lists rather than in the space of feasible schedules. As an illustration of their usefulness, a priority list based simulated annealing heuristic is presented, which, although simple, is competitive with the current leading schedule based simulated annealing and tabu search heuristics.

Suggested Citation

  • P M E Shutler, 2003. "A priority list based heuristic for the job shop problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(6), pages 571-584, June.
    • Handle: RePEc:pal:jorsoc:v:54:y:2003:i:6:d:10.1057_palgrave.jors.2601481
    DOI: 10.1057/palgrave.jors.2601481
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    References listed on IDEAS

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    Cited by:

    1. G I Zobolas & C D Tarantilis & G Ioannou, 2009. "A hybrid evolutionary algorithm for the job shop scheduling problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(2), pages 221-235, February.
    2. Zamani, Reza & Lau, Sim Kim, 2010. "Embedding learning capability in Lagrangean relaxation: An application to the travelling salesman problem," European Journal of Operational Research, Elsevier, vol. 201(1), pages 82-88, February.
    3. Paul M E Shutler, 2004. "A priority list based heuristic for the job shop problem: part 2 tabu search," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(7), pages 780-784, July.
    4. B Suman & P Kumar, 2006. "A survey of simulated annealing as a tool for single and multiobjective optimization," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(10), pages 1143-1160, October.

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