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No-Idle Flowshop Scheduling for Energy-Efficient Production: An Improved Optimization Framework

Author

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  • Chen-Yang Cheng

    (Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei 106, Taiwan
    These authors contributed equally to this work; Shih-Wei Lin is the co-first author.)

  • Shih-Wei Lin

    (Department of Information Management, Chang Gung University, Taoyuan 333, Taiwan
    Department of Neurology, Linkou Chang Gung Memorial Hospital, Taoyuan 333, Taiwan
    Department of Industrial Engineering and Management, Ming Chi University of Technology, New Taipei 243, Taiwan
    These authors contributed equally to this work; Shih-Wei Lin is the co-first author.)

  • Pourya Pourhejazy

    (Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei 106, Taiwan
    These authors contributed equally to this work; Shih-Wei Lin is the co-first author.)

  • Kuo-Ching Ying

    (Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei 106, Taiwan
    These authors contributed equally to this work; Shih-Wei Lin is the co-first author.)

  • Yu-Zhe Lin

    (Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei 106, Taiwan
    Taiwan Semiconductor Manufacturing Company Limited, Hsinchu Science Park, Hsinchu 30078, Taiwan)

Abstract

Production environment in modern industries, like integrated circuits manufacturing, fiberglass processing, steelmaking, and ceramic frit, is characterized by zero idle-time between inbound and outbound jobs on every machine; this technical requirement improves energy efficiency, hence, has implications for cleaner production in other production situations. An exhaustive review of literature is first conducted to shed light on the development of no-idle flowshops. Considering the intractable nature of the problem, this research also develops an extended solution method for optimizing the Bi-objective No-Idle Permutation Flowshop Scheduling Problem (BNIPFSP). Extensive numerical tests and statistical analysis are conducted to evaluate the developed method, comparing it with the best-performing algorithm developed to solve the BNIPFSP. Overall, the proposed extension outperforms in terms of solution quality at the expense of a longer computational time. This research is concluded by providing suggestions for the future development of this understudied scheduling extension.

Suggested Citation

  • Chen-Yang Cheng & Shih-Wei Lin & Pourya Pourhejazy & Kuo-Ching Ying & Yu-Zhe Lin, 2021. "No-Idle Flowshop Scheduling for Energy-Efficient Production: An Improved Optimization Framework," Mathematics, MDPI, vol. 9(12), pages 1-18, June.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:12:p:1335-:d:572153
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    References listed on IDEAS

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    1. Aghelinejad, MohammadMohsen & Ouazene, Yassine & Yalaoui, Alice, 2019. "Complexity analysis of energy-efficient single machine scheduling problems," Operations Research Perspectives, Elsevier, vol. 6(C).
    2. Yu, Shiwei & Wei, Yi-Ming & Guo, Haixiang & Ding, Liping, 2014. "Carbon emission coefficient measurement of the coal-to-power energy chain in China," Applied Energy, Elsevier, vol. 114(C), pages 290-300.
    3. Mansouri, S. Afshin & Aktas, Emel & Besikci, Umut, 2016. "Green scheduling of a two-machine flowshop: Trade-off between makespan and energy consumption," European Journal of Operational Research, Elsevier, vol. 248(3), pages 772-788.
    4. Osman, IH & Potts, CN, 1989. "Simulated annealing for permutation flow-shop scheduling," Omega, Elsevier, vol. 17(6), pages 551-557.
    5. Foumani, Mehdi & Smith-Miles, Kate, 2019. "The impact of various carbon reduction policies on green flowshop scheduling," Applied Energy, Elsevier, vol. 249(C), pages 300-315.
    6. Fernando Luis Rossi & Marcelo Seido Nagano, 2021. "Heuristics for the mixed no-idle flowshop with sequence-dependent setup times," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 72(2), pages 417-443, February.
    7. Pagnozzi, Federico & Stützle, Thomas, 2021. "Automatic design of hybrid stochastic local search algorithms for permutation flowshop problems with additional constraints," Operations Research Perspectives, Elsevier, vol. 8(C).
    8. Ruiz, Ruben & Stutzle, Thomas, 2007. "A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 177(3), pages 2033-2049, March.
    9. Jian-Ya Ding & Shiji Song & Jatinder N.D. Gupta & Cheng Wang & Rui Zhang & Cheng Wu, 2016. "New block properties for flowshop scheduling with blocking and their application in an iterated greedy algorithm," International Journal of Production Research, Taylor & Francis Journals, vol. 54(16), pages 4759-4772, August.
    10. Nawaz, Muhammad & Enscore Jr, E Emory & Ham, Inyong, 1983. "A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem," Omega, Elsevier, vol. 11(1), pages 91-95.
    11. Taillard, E., 1993. "Benchmarks for basic scheduling problems," European Journal of Operational Research, Elsevier, vol. 64(2), pages 278-285, January.
    12. Chen Peng & Tao Peng & Yi Zhang & Renzhong Tang & Luoke Hu, 2018. "Minimising Non-Processing Energy Consumption and Tardiness Fines in a Mixed-Flow Shop," Energies, MDPI, vol. 11(12), pages 1-15, December.
    13. Zhu, Zhi-Shuang & Liao, Hua & Cao, Huai-Shu & Wang, Lu & Wei, Yi-Ming & Yan, Jinyue, 2014. "The differences of carbon intensity reduction rate across 89 countries in recent three decades," Applied Energy, Elsevier, vol. 113(C), pages 808-815.
    14. Tolga Bektaş & Alper Hamzadayı & Rubén Ruiz, 2020. "Benders decomposition for the mixed no-idle permutation flowshop scheduling problem," Journal of Scheduling, Springer, vol. 23(4), pages 513-523, August.
    15. Pan, Quan-Ke & Ruiz, Rubén, 2014. "An effective iterated greedy algorithm for the mixed no-idle permutation flowshop scheduling problem," Omega, Elsevier, vol. 44(C), pages 41-50.
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    Cited by:

    1. Fernando Luis Rossi & Marcelo Seido Nagano, 2022. "Beam search-based heuristics for the mixed no-idle flowshop with total flowtime criterion," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(4), pages 1311-1346, December.

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