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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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    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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