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An Instance Generator for Scheduling Problems Featuring Options for Unequal Stages and Unequal Parallel Machines

Author

Listed:
  • Jakkrit Latthawanichphan

    (King Mongkuts University of Technology North Bangkok, Bangkok, Thailand)

  • Watchara Songserm

    (King Mongkuts University of Technology North Bangkok, Bangkok, Thailand)

  • Teeradej Wuttipornpun

    (King Mongkuts University of Technology North Bangkok, Bangkok, Thailand)

Abstract

This research aims to develop a new Instance Generator for Scheduling Problems (IGSP). There are three main features differentiating IGSP generator from extant Instance Generators (IGs). Firstly, the IGSP can generate datasets for various types of production shop (single machine, parallel machines, flow shop, and job shop), while the extant IGs can generate datasets for only a specific production shop. Secondly, for the multi-stage problem, in the case of a flow shop and job shop, a number of stages of each job can be unequal. Finally, a number of parallel machines in each stage of the multi-stage problem can be unequal. The final two features make datasets obtained by the IGSP more realistic than the extant IGs. In addition, IGSP features a comprehensive graphical user interface and well-organised output text files. Researchers can use it to evaluate the performances of their scheduling algorithms and determine benchmark problem instances.

Suggested Citation

  • Jakkrit Latthawanichphan & Watchara Songserm & Teeradej Wuttipornpun, 2019. "An Instance Generator for Scheduling Problems Featuring Options for Unequal Stages and Unequal Parallel Machines," International Journal of Technology and Engineering Studies, PROF.IR.DR.Mohid Jailani Mohd Nor, vol. 5(4), pages 106-112.
    • Handle: RePEc:apa:ijtess:2019:p:106-112
    DOI: 10.20469/ijtes.5.10001-4
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