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A hybrid particle swarm optimization algorithm for a no-wait flow shop scheduling problem with the total flow time

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Abstract

This paper proposes a particle swarm optimization (PSO) algorithm based on memetic algorithm (MA) that hybridizes with a local search method for solving a no-wait flow shop scheduling problem. The main objective is to minimize the total flow time. Within the framework of the proposed algorithm, a local version of PSO with a ring-shape topology structure is used as global search. In addition, a self-organized random immigrant's scheme is extended into our proposed algorithm in order to further enhance its exploration capacity for new peaks in search space. The experimental study over the moving peaks benchmark problem shows that the proposed PSO-based MA is robust. Finally, the analysis of the computational results and conclusion are given.

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Authors and Affiliations

  1. Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

    M. Akhshabi

  2. School of Industrial Engineering and Center of Excellence for Intelligence Based Experimental Mechanics, College of Engineering, University of Tehran, Tehran, Iran

    R. Tavakkoli-Moghaddam

  3. Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran

    F. Rahnamay-Roodposhti

Authors
  1. M. Akhshabi
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  2. R. Tavakkoli-Moghaddam
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  3. F. Rahnamay-Roodposhti
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Correspondence to M. Akhshabi.

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Akhshabi, M., Tavakkoli-Moghaddam, R. & Rahnamay-Roodposhti, F. A hybrid particle swarm optimization algorithm for a no-wait flow shop scheduling problem with the total flow time. Int J Adv Manuf Technol 70, 1181–1188 (2014). https://doi.org/10.1007/s00170-013-5351-9

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