A Joint Scheduling of Production and Distribution Operations in a Flow Shop Manufacturing System

Document Type : Article

Authors

1 Department of Industrial Engineering, K.N. Toosi University of Technology, Tehran, Iran

2 Department of Industrial Engineering, K.N. Toosi University of Technology, Tehran, Iran.

Abstract

In traditional scheduling problems and in many real-world applications the production operations are scheduled regardless of distribution decisions. Indeed, the completion time of a job in such problems is traditionally defined as the time when the production sequences of a job are finished. However, in many practical environments completed orders are delivered to customers immediately after production stages without any further inventory storage. Therefore, in this paper, we investigate an integrated scheduling model of production and distribution problems simultaneously. It is assumed that products are proceed through a permutation flow shop scheduling manufacturing system and delivered to customers via available vehicles. The objective in our integrated model is to minimize maximum returning time (MRT), which is the time that last vehicle delivers last order to relevant customer and returns to production center. The problem formulated mathematically, and then an improved imperialist competitive algorithm (I-ICA) is proposed for solving it. Furthermore, sufficient numbers of test problems are generated for computational study. Various parameters of the algorithm are analyzed to calibrate the algorithm by means of the Taguchi method. At the end, the effectiveness of the proposed model and suggested algorithm is evaluated through a computational study where obtained results show the appropriate performance of integrated model and solving approach with regard to the other algorithms.

Keywords

Main Subjects

References

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Scientia Iranica
Volume 25, Issue 2
Transactions on Industrial Engineering (E)
March and April 2018
Pages 911-930

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History

  • Receive Date: 29 May 2016
  • Revise Date: 30 October 2016
  • Accept Date: 18 December 2016

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