Modeling and Solving Flow Shop Scheduling Problem Considering Worker Resource

Authors

  • Paria Samadi Parviznejad * Phd Candidate, Faculty of Management, University of Tehran, Tehran, Iran,
  • Ezzatollah Asgharizadeh Faculty of Management, University of Tehran, Tehran, Iran

DOI:

https://doi.org/10.59615/ijie.1.4.1

DOR:

https://dorl.net/dor/20.1001.1.27831906.2021.1.4.1.9

Keywords:

Fuzzy, Uncertainty, Flow shop Scheduling

Abstract

In this paper, an uninterrupted hybrid flow scheduling problem is modeled under uncertainty conditions. Due to the uncertainty of processing time in workshops, fuzzy programming method has been used to control the parameters of processing time and preparation time. In the proposed model, there are several jobs that must be processed by machines and workers, respectively. The main purpose of the proposed model is to determine the correct sequence of operations and assign operations to each machine and each worker at each stage, so that the total completion time (Cmax) is minimized. Also this paper, fuzzy programming method is used for control unspecified parameter has been used from GAMS software to solve sample problems. The results of problem solving in small and medium dimensions show that with increasing uncertainty, the amount of processing time and consequently the completion time increases. Increases from the whole work. On the other hand, with the increase in the number of machines and workers in each stage due to the high efficiency of the machines, the completion time of all works has decreased. Innovations in this paper include uninterrupted hybrid flow storage scheduling with respect to fuzzy processing time and preparation time in addition to payment time. The allocation of workers and machines to jobs is another innovation of this article.

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Published

2021-12-28

How to Cite

Samadi Parviznejad, P., & Asgharizadeh, E. . (2021). Modeling and Solving Flow Shop Scheduling Problem Considering Worker Resource. International Journal of Innovation in Engineering, 1(4), 1–17. https://doi.org/10.59615/ijie.1.4.1

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Section

Original Research