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A hybrid algorithm based on particle swarm optimization and simulated annealing for a periodic job shop scheduling problem

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Abstract

Generating schedules such that all operations are repeated every constant period of time is as important as generating schedules with minimum delays in all cases where a known discipline is desired or obligated by stakeholders. In this paper, a periodic job shop scheduling problem (PJSSP) based on the periodic event scheduling problem (PESP) is presented, which deviates from the cyclic scheduling. The PESP schedules a number of recurring events as such that each pair of event fulfills certain constraints during a given fixed time period. To solve such a hard PJSS problem, we propose a hybrid algorithm, namely PSO-SA, based on particle swarm optimization (PSO) and simulated annealing (SA) algorithms. To evaluate this proposed PSO-SA, we carry out some randomly constructed instances by which the related results are compared with the proposed SA and PSO algorithms as well as a branch-and-bound algorithm. In addition, we compare the results with a hybrid algorithm embedded with electromagnetic-like mechanism and SA. Moreover, three lower bounds (LBs) are studied, and the gap between the found LBs and the best found solutions are reported. The outcomes prove that the proposed hybrid algorithm is an efficient and effective tool to solve the PJSSP.

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Authors and Affiliations

  1. Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

    Amin Jamili & Mohammad Ali Shafia

  2. Department of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran

    Reza Tavakkoli-Moghaddam

Authors
  1. Amin Jamili
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  2. Mohammad Ali Shafia
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  3. Reza Tavakkoli-Moghaddam
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Correspondence to Amin Jamili.

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Jamili, A., Shafia, M.A. & Tavakkoli-Moghaddam, R. A hybrid algorithm based on particle swarm optimization and simulated annealing for a periodic job shop scheduling problem. Int J Adv Manuf Technol 54, 309–322 (2011). https://doi.org/10.1007/s00170-010-2932-8

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  • DOI: https://doi.org/10.1007/s00170-010-2932-8

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