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A Multiobjective Optimization Approach for Multiobjective Hybrid Flowshop Green Scheduling with Consistent Sublots

Author

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  • Weiwei Wang

    (School of Computer Science, Liaocheng University, Liaocheng 252000, China)

  • Biao Zhang

    (School of Computer Science, Liaocheng University, Liaocheng 252000, China)

  • Baoxian Jia

    (School of Computer Science, Liaocheng University, Liaocheng 252000, China)

Abstract

Hybrid flowshop scheduling problems are encountered in many real-world manufacturing scenarios. With increasingly fierce market competition, the production mode of multiple varieties and small batches has gradually been accepted by enterprises, where the technology of lot streaming is widely used. Meanwhile, green criteria, such as energy consumption and carbon emissions, have attracted increasing attention to improving protection awareness. With these motivations, this paper studies a multiobjective hybrid flowshop green scheduling problem with consistent sublots (MOHFGSP_CS), aiming to minimize two objectives, i.e., makespan and total energy consumption, simultaneously. To solve this complex problem, we first formulate a novel multiobjective optimization model. However, due to the NP-hard nature of the problem, the model is computationally prohibitive as the problem scale increases. Thus, a multiobjective discrete artificial bee colony algorithm (MDABC) based on decomposition is proposed. There are three phases in this algorithm: the VND-based employed bee phase, the adjustment weight onlooker bee phase, and the population interaction scout bee phase. In the experimental study, various small-scale and large-scale instances are collected to verify the effectiveness of the multiobjective optimization model and the MDABC. Comprehensive computational comparisons and statistical analysis show that the developed strategies and MDABC show superior performance.

Suggested Citation

  • Weiwei Wang & Biao Zhang & Baoxian Jia, 2023. "A Multiobjective Optimization Approach for Multiobjective Hybrid Flowshop Green Scheduling with Consistent Sublots," Sustainability, MDPI, vol. 15(3), pages 1-29, February.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:3:p:2622-:d:1054375
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    References listed on IDEAS

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    1. Ruiz, Rubén & Vázquez-Rodríguez, José Antonio, 2010. "The hybrid flow shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 205(1), pages 1-18, August.
    2. Kim, J-S. & Kang, S-H. & Lee, S. M., 1997. "Transfer batch scheduling for a two-stage flowshop with identical parallel machines at each stage," Omega, Elsevier, vol. 25(5), pages 547-555, October.
    3. Pan, Quan-Ke & Gao, Liang & Li, Xin-Yu & Gao, Kai-Zhou, 2017. "Effective metaheuristics for scheduling a hybrid flowshop with sequence-dependent setup times," Applied Mathematics and Computation, Elsevier, vol. 303(C), pages 89-112.
    4. Guo-Zhong Fu & Tianda Yu & Wei Li & Qiang Deng & Bo Yang, 2021. "A Decomposition-Based Multiobjective Optimization Evolutionary Algorithm with Adaptive Weight Generation Strategy," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-12, September.
    5. Ding, Jian-Ya & Song, Shiji & Wu, Cheng, 2016. "Carbon-efficient scheduling of flow shops by multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 248(3), pages 758-771.
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