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OSGA: genetic-based open-shop scheduling with consideration of machine maintenance in small and medium enterprises

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  • Shahaboddin Shamshirband
  • Mohammad Shojafar
  • A. Hosseinabadi
  • Maryam Kardgar
  • M. Nasir
  • Rodina Ahmad

Abstract

The problem of open-shop scheduling includes a set of activities which must be performed on a limited set of machines. The goal of scheduling in open-shop is the presentation of a scheduled program for performance of the whole operation, so that the ending performance time of all job operations will be minimised. The open-shop scheduling problem can be solved in polynomial time when all nonzero processing times are equal, becoming equivalent to edge coloring that has the jobs and workstations as its vertices and that has an edge for every job-workstation pair with a nonzero processing time. For three or more workstations, or three or more jobs, with varying processing times, open-shop scheduling is NP-hard. Different algorithms have been presented for open-shop scheduling so far. However, most of these algorithms have not considered the machine maintenance problem. Whilst in production level, each machine needs maintenance, and this directly influences the assurance reliability of the system. In this paper, a new genetic-based algorithm to solve the open-shop scheduling problem, namely OSGA, is developed. OSGA considers machine maintenance. To confirm the performance of OSGA, it is compared with DGA, SAGA and TSGA algorithms. It is observed that OSGA performs quite well in terms of solution quality and efficiency in small and medium enterprises (SMEs). The results support the efficiency of the proposed method for solving the open-shop scheduling problem, particularly considering machine maintenance especially in SMEs’. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Shahaboddin Shamshirband & Mohammad Shojafar & A. Hosseinabadi & Maryam Kardgar & M. Nasir & Rodina Ahmad, 2015. "OSGA: genetic-based open-shop scheduling with consideration of machine maintenance in small and medium enterprises," Annals of Operations Research, Springer, vol. 229(1), pages 743-758, June.
    • Handle: RePEc:spr:annopr:v:229:y:2015:i:1:p:743-758:10.1007/s10479-015-1855-z
    DOI: 10.1007/s10479-015-1855-z
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    1. Taillard, E., 1993. "Benchmarks for basic scheduling problems," European Journal of Operational Research, Elsevier, vol. 64(2), pages 278-285, January.
    2. Munier-Kordon, Alix & Rebaine, Djamal, 2010. "The two-machine open-shop problem with unit-time operations and time delays to minimize the makespan," European Journal of Operational Research, Elsevier, vol. 203(1), pages 42-49, May.
    3. Matta, Marie E. & Elmaghraby, Salah E., 2010. "Polynomial time algorithms for two special classes of the proportionate multiprocessor open shop," European Journal of Operational Research, Elsevier, vol. 201(3), pages 720-728, March.
    4. Gueret, Christelle & Prins, Christian, 1998. "Classical and new heuristics for the open-shop problem: A computational evaluation," European Journal of Operational Research, Elsevier, vol. 107(2), pages 306-314, June.
    5. Ali Hosseinabadi & Hajar Siar & Shahaboddin Shamshirband & Mohammad Shojafar & Mohd Nasir, 2015. "Using the gravitational emulation local search algorithm to solve the multi-objective flexible dynamic job shop scheduling problem in Small and Medium Enterprises," Annals of Operations Research, Springer, vol. 229(1), pages 451-474, June.
    6. Christian Prins, 2000. "Competitive genetic algorithms for the open-shop scheduling problem," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 52(3), pages 389-411, December.
    7. Lin, Hung-Tso & Lee, Hong-Tau & Pan, Wen-Jung, 2008. "Heuristics for scheduling in a no-wait open shop with movable dedicated machines," International Journal of Production Economics, Elsevier, vol. 111(2), pages 368-377, February.
    8. David Alcaide & Joaquín Sicilia & Daniele Vigo, 1997. "A tabu search algorithm for the Open Shop problem," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 5(2), pages 283-296, December.
    9. Liaw, Ching-Fang, 2000. "A hybrid genetic algorithm for the open shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 124(1), pages 28-42, July.
    10. Yu, Wei & Liu, Zhaohui & Wang, Leiyang & Fan, Tijun, 2011. "Routing open shop and flow shop scheduling problems," European Journal of Operational Research, Elsevier, vol. 213(1), pages 24-36, August.
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    Cited by:

    1. Xin Yang & Zhenxiang Zeng & Ruidong Wang & Xueshan Sun, 2016. "Bi-Objective Flexible Job-Shop Scheduling Problem Considering Energy Consumption under Stochastic Processing Times," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-13, December.

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