IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i9p5072-d800215.html
   My bibliography  Save this article

Adaptive Genetic Algorithm Based on Fuzzy Reasoning for the Multilevel Capacitated Lot-Sizing Problem with Energy Consumption in Synchronizer Production

Author

Listed:
  • Shuai Wang

    (Institute of Intelligent Manufacturing Systems, Chang’an University, Xi’an 710064, China)

  • Jizhuang Hui

    (Institute of Intelligent Manufacturing Systems, Chang’an University, Xi’an 710064, China)

  • Bin Zhu

    (Institute of Intelligent Manufacturing Systems, Chang’an University, Xi’an 710064, China)

  • Ying Liu

    (Institute of Mechanical and Manufacturing Engineering, School of Engineering, Cardiff University, Cardiff CF24 3AA, UK)

Abstract

The multilevel capacitated lot-sizing problem (MLCLSP) is a vital theoretical problem of production planning in discrete manufacturing. An improved algorithm based on the genetic algorithm (GA) is proposed to solve the MLCLSP. Based on the solution results, the distribution of energy consumption in a synchronous production case is analyzed. In the related literature, the GA has become a much-discussed topic in solving these kinds of problems. Although the standard GA can make up for the defects of the traditional algorithm, it will lead to the problems of unstable solution results and easy local convergence. For these reasons, this research presents an adaptive genetic algorithm based on fuzzy theory (fuzzy-GA) to solve the MLCLSP. Firstly, the solving process of the MLCLSP with the fuzzy-GA is described in detail, where algorithms for key technologies such as the capacity constraint algorithm and the algorithm of solving fitness value are developed. Secondly, the auto-encoding of decision variables for MLCLSPs is studied; within this, the decision variables of whether to produce or not are encoded into a hierarchical structure based on the bill of material; combined with external demand, the decision variables of lot-sizing are constructed. Thirdly, the adaptive optimization process of parameters of the GA for the MLCLSP based on fuzzy theory is expounded, in which membership function, fuzzy rule, and defuzzification of the MLCLSP is mainly presented. Experimental studies using the processed dataset collected from a synchronizer manufacturer have demonstrated the merits of the proposed approach, in which the energy consumption distribution of the optimized production plan is given. The optimal lot-sizing is closer to the average value of the optimal value compared with the standard GA, which indicates that the proposed fuzzy-GA approach has better convergence and stability.

Suggested Citation

  • Shuai Wang & Jizhuang Hui & Bin Zhu & Ying Liu, 2022. "Adaptive Genetic Algorithm Based on Fuzzy Reasoning for the Multilevel Capacitated Lot-Sizing Problem with Energy Consumption in Synchronizer Production," Sustainability, MDPI, vol. 14(9), pages 1-24, April.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:9:p:5072-:d:800215
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/9/5072/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/9/5072/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Boonmee, Atiwat & Sethanan, Kanchana, 2016. "A GLNPSO for multi-level capacitated lot-sizing and scheduling problem in the poultry industry," European Journal of Operational Research, Elsevier, vol. 250(2), pages 652-665.
    2. Kirschstein, Thomas & Meisel, Frank, 2019. "A multi-period multi-commodity lot-sizing problem with supplier selection, storage selection and discounts for the process industry," European Journal of Operational Research, Elsevier, vol. 279(2), pages 393-406.
    3. MILLER, Andrew & NEMHAUSER, George & SAVELSBERGH, Martin, 2000. "Solving multi-item capacitated lot-sizing problems with setup times by branch-and-cut," LIDAM Discussion Papers CORE 2000039, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Marcos Mansano Furlan & Maristela Oliveira Santos, 2017. "BFO: a hybrid bees algorithm for the multi-level capacitated lot-sizing problem," Journal of Intelligent Manufacturing, Springer, vol. 28(4), pages 929-944, April.
    5. Jia, Shun & Yuan, Qinghe & Lv, Jingxiang & Liu, Ying & Ren, Dawei & Zhang, Zhongwei, 2017. "Therblig-embedded value stream mapping method for lean energy machining," Energy, Elsevier, vol. 138(C), pages 1081-1098.
    6. Wu, Tao & Shi, Leyuan & Geunes, Joseph & AkartunalI, Kerem, 2011. "An optimization framework for solving capacitated multi-level lot-sizing problems with backlogging," European Journal of Operational Research, Elsevier, vol. 214(2), pages 428-441, October.
    7. Chen, Haoxun, 2015. "Fix-and-optimize and variable neighborhood search approaches for multi-level capacitated lot sizing problems," Omega, Elsevier, vol. 56(C), pages 25-36.
    8. Jia, Shun & Cai, Wei & Liu, Conghu & Zhang, Zhongwei & Bai, Shuowei & Wang, Qiuyan & Li, Shuoshuo & Hu, Luoke, 2021. "Energy modeling and visualization analysis method of drilling processes in the manufacturing industry," Energy, Elsevier, vol. 228(C).
    9. Berretta, Regina & Rodrigues, Luiz Fernando, 2004. "A memetic algorithm for a multistage capacitated lot-sizing problem," International Journal of Production Economics, Elsevier, vol. 87(1), pages 67-81, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wei, Mingyuan & Qi, Mingyao & Wu, Tao & Zhang, Canrong, 2019. "Distance and matching-induced search algorithm for the multi-level lot-sizing problem with substitutable bill of materials," European Journal of Operational Research, Elsevier, vol. 277(2), pages 521-541.
    2. Gruson, Matthieu & Cordeau, Jean-François & Jans, Raf, 2021. "Benders decomposition for a stochastic three-level lot sizing and replenishment problem with a distribution structure," European Journal of Operational Research, Elsevier, vol. 291(1), pages 206-217.
    3. Almeder, Christian & Klabjan, Diego & Traxler, Renate & Almada-Lobo, Bernardo, 2015. "Lead time considerations for the multi-level capacitated lot-sizing problem," European Journal of Operational Research, Elsevier, vol. 241(3), pages 727-738.
    4. Shun Jia & Shang Wang & Jingxiang Lv & Wei Cai & Na Zhang & Zhongwei Zhang & Shuowei Bai, 2021. "Multi-Objective Optimization of CNC Turning Process Parameters Considering Transient-Steady State Energy Consumption," Sustainability, MDPI, vol. 13(24), pages 1-23, December.
    5. Tao Wu, 2022. "Predictive Search for Capacitated Multi-Item Lot Sizing Problems," INFORMS Journal on Computing, INFORMS, vol. 34(1), pages 385-406, January.
    6. Zhiqiang Yan & Jian Huang & Jingxiang Lv & Jizhuang Hui & Ying Liu & Hao Zhang & Enhuai Yin & Qingtao Liu, 2022. "A New Method of Predicting the Energy Consumption of Additive Manufacturing considering the Component Working State," Sustainability, MDPI, vol. 14(7), pages 1-23, March.
    7. Sereshti, Narges & Adulyasak, Yossiri & Jans, Raf, 2024. "Managing flexibility in stochastic multi-level lot sizing problem with service level constraints," Omega, Elsevier, vol. 122(C).
    8. Tatiana N. Ivanova & Witold Biały & Aleksander I. Korshunov & Jerzy Jura & Krzysztof Kaczmarczyk & Krzysztof Turczyński, 2022. "Increasing Energy Efficiency in Well Drilling," Energies, MDPI, vol. 15(5), pages 1-16, March.
    9. He, Yan & Wu, Tao & Zhang, Canrong & Liang, Zhe, 2015. "An improved MIP heuristic for the intermodal hub location problem," Omega, Elsevier, vol. 57(PB), pages 203-211.
    10. Shun Jia & Qingwen Yuan & Wei Cai & Qinghe Yuan & Conghu Liu & Jingxiang Lv & Zhongwei Zhang, 2018. "Establishment of an Improved Material-Drilling Power Model to Support Energy Management of Drilling Processes," Energies, MDPI, vol. 11(8), pages 1-16, August.
    11. Wang, Jinling & Tian, Yebing & Hu, Xintao & Han, Jinguo & Liu, Bing, 2023. "Integrated assessment and optimization of dual environment and production drivers in grinding," Energy, Elsevier, vol. 272(C).
    12. Tao Wu & Zhe Liang & Canrong Zhang, 2018. "Analytics Branching and Selection for the Capacitated Multi-Item Lot Sizing Problem with Nonidentical Machines," INFORMS Journal on Computing, INFORMS, vol. 30(2), pages 236-258, May.
    13. Almeder, Christian, 2010. "A hybrid optimization approach for multi-level capacitated lot-sizing problems," European Journal of Operational Research, Elsevier, vol. 200(2), pages 599-606, January.
    14. Mohammad Khosroabadi & Jafar Gheidar-Kheljani & Mohammad Hosein Karimi Gavareshki, 2024. "Utilizing Multi-vehicle Traveling Purchaser Problem for Multiple-Supplier Selection and Multi-period Lot-Sizing in a Fuzzy Demand Environment," SN Operations Research Forum, Springer, vol. 5(4), pages 1-28, December.
    15. Yves Pochet & Mathieu Van Vyve, 2004. "A General Heuristic for Production Planning Problems," INFORMS Journal on Computing, INFORMS, vol. 16(3), pages 316-327, August.
    16. Helber, Stefan & Sahling, Florian, 2010. "A fix-and-optimize approach for the multi-level capacitated lot sizing problem," International Journal of Production Economics, Elsevier, vol. 123(2), pages 247-256, February.
    17. Gansterer, Margaretha & Födermayr, Patrick & Hartl, Richard F., 2021. "The capacitated multi-level lot-sizing problem with distributed agents," International Journal of Production Economics, Elsevier, vol. 235(C).
    18. Boonmee, Atiwat & Sethanan, Kanchana, 2016. "A GLNPSO for multi-level capacitated lot-sizing and scheduling problem in the poultry industry," European Journal of Operational Research, Elsevier, vol. 250(2), pages 652-665.
    19. Wang, Fa & Chen, Jing & Yang, Hui & Yu, Bo, 2022. "Supplier selection with information disclosure in the presence of uninformed consumers," International Journal of Production Economics, Elsevier, vol. 243(C).
    20. Murat Gunduz & Ayman Fahmi Naser, 2017. "Cost Based Value Stream Mapping as a Sustainable Construction Tool for Underground Pipeline Construction Projects," Sustainability, MDPI, vol. 9(12), pages 1-20, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:9:p:5072-:d:800215. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.