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Evolutionary algorithms for multi-objective dual-resource constrained flexible job-shop scheduling problem

Author

Listed:
  • M. Yazdani

    (Islamic Azad University)

  • M. Zandieh

    (Shahid Beheshti University, G.C.)

  • R. Tavakkoli-Moghaddam

    (University of Tehran)

Abstract

This paper presents a multi-objective dual-resource constrained flexible job-shop scheduling problem (MODRCFJSP) with the objectives of minimizing the makespan, critical machine workload and total workload of machines simultaneously. Two types of multi-objective evolutionary algorithms including fast elitist non-dominated sorting genetic algorithm (NSGA-II) and non-dominated ranking genetic algorithm (NRGA) are proposed for solving MODRCFJSP. Some efficient mutation and crossover operators are adapted to the special chromosome structure of the problem for producing new solutions in the algorithm’s generations. Besides, we provide controlled elitism based version of NSGA-II and NRGA, namely controlled elitist NSGA-II (CENSGA-II) and controlled elitist NRGA (CENRGA), to optimize MODRCFJSP. To show the performance of the four proposed algorithms, numerical experiments with randomly generated test problems are used. Moreover, different convergence and diversity performance metrics are employed to illustrate the relative performance of the presented algorithms.

Suggested Citation

  • M. Yazdani & M. Zandieh & R. Tavakkoli-Moghaddam, 2019. "Evolutionary algorithms for multi-objective dual-resource constrained flexible job-shop scheduling problem," OPSEARCH, Springer;Operational Research Society of India, vol. 56(3), pages 983-1006, September.
    • Handle: RePEc:spr:opsear:v:56:y:2019:i:3:d:10.1007_s12597-019-00395-y
    DOI: 10.1007/s12597-019-00395-y
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    References listed on IDEAS

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    1. Xiao-long Zheng & Ling Wang, 2016. "A knowledge-guided fruit fly optimization algorithm for dual resource constrained flexible job-shop scheduling problem," International Journal of Production Research, Taylor & Francis Journals, vol. 54(18), pages 5554-5566, September.
    2. Khalili-Damghani, Kaveh & Abtahi, Amir-Reza & Tavana, Madjid, 2013. "A new multi-objective particle swarm optimization method for solving reliability redundancy allocation problems," Reliability Engineering and System Safety, Elsevier, vol. 111(C), pages 58-75.
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    Cited by:

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    2. Geurtsen, M. & Didden, Jeroen B.H.C. & Adan, J. & Atan, Z. & Adan, I., 2023. "Production, maintenance and resource scheduling: A review," European Journal of Operational Research, Elsevier, vol. 305(2), pages 501-529.
    3. Mohamadreza Dabiri & Mehdi Yazdani & Bahman Naderi & Hassan Haleh, 2022. "Modeling and solution methods for hybrid flow shop scheduling problem with job rejection," Operational Research, Springer, vol. 22(3), pages 2721-2765, July.
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    5. Nikzamir, Mohammad & Baradaran, Vahid, 2020. "A healthcare logistic network considering stochastic emission of contamination: Bi-objective model and solution algorithm," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).

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