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Hybrid Rollout Approaches for the Job Shop Scheduling Problem

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  • F. Guerriero

    (Università della Calabria)

Abstract

In this paper, we focus on heuristic approaches for solving the deterministic job shop scheduling problem. More specifically, a new priority dispatch rule and hybrid rollout algorithms are developed for approaching the problem under consideration. The proposed solution algorithms are tested on a set of instances taken from the literature and compared with other methods. The computational results validate the effectiveness of the developed solution approaches and show that the proposed rollout algorithms are competitive with respect to several state-of-art heuristics for solving the job shop scheduling problem.

Suggested Citation

  • F. Guerriero, 2008. "Hybrid Rollout Approaches for the Job Shop Scheduling Problem," Journal of Optimization Theory and Applications, Springer, vol. 139(2), pages 419-438, November.
    • Handle: RePEc:spr:joptap:v:139:y:2008:i:2:d:10.1007_s10957-008-9362-x
    DOI: 10.1007/s10957-008-9362-x
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    References listed on IDEAS

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    Cited by:

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    2. Luca Bertazzi, 2012. "Minimum and Worst-Case Performance Ratios of Rollout Algorithms," Journal of Optimization Theory and Applications, Springer, vol. 152(2), pages 378-393, February.
    3. Bertazzi, Luca & Bosco, Adamo & Laganà, Demetrio, 2015. "Managing stochastic demand in an Inventory Routing Problem with transportation procurement," Omega, Elsevier, vol. 56(C), pages 112-121.
    4. Zhenyuan Liu & Jiongbing Lu & Zaisheng Liu & Guangrui Liao & Hao Howard Zhang & Junwu Dong, 2019. "Patient scheduling in hemodialysis service," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 337-362, January.

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