IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v196y2018icp269-283.html
   My bibliography  Save this article

A three-layer chromosome genetic algorithm for multi-cell scheduling with flexible routes and machine sharing

Author

Listed:
  • Feng, Yanling
  • Li, Guo
  • Sethi, Suresh P.

Abstract

Alternative machines assignment, machine sharing, and inter-cell movements are very common yet difficult to be solved integratedly in modern dynamic Cellular Manufacturing Systems (CMS). In this paper, we incorporate these issues and consider a dynamic cellular scheduling problem with flexible routes and machine sharing. We employ a mixed integer programming scheduling model to minimize both the makespan and the total workload. To solve this new model, we propose a three-layer chromosome genetic algorithm (TCGA). We first compare the performances of the proposed TCGA with the optimal solution obtained by CPLEX. Computational results show that the TCGA performs well within a reasonable amount of time. We further compare our proposed TCGA with the classic genetic algorithm (GA) and the shortest processing time (SPT) rule through numerical experiments. The results reveal that the TCGA significantly improves the performance and effectively balances the workload of machines.

Suggested Citation

  • Feng, Yanling & Li, Guo & Sethi, Suresh P., 2018. "A three-layer chromosome genetic algorithm for multi-cell scheduling with flexible routes and machine sharing," International Journal of Production Economics, Elsevier, vol. 196(C), pages 269-283.
    • Handle: RePEc:eee:proeco:v:196:y:2018:i:c:p:269-283
    DOI: 10.1016/j.ijpe.2017.12.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527317304097
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijpe.2017.12.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Gonçalves, José Fernando & Resende, Mauricio G.C., 2015. "A biased random-key genetic algorithm for the unequal area facility layout problem," European Journal of Operational Research, Elsevier, vol. 246(1), pages 86-107.
    2. Antonio Costa & Fulvio Antonio Cappadonna & Sergio Fichera, 2017. "A hybrid genetic algorithm for minimizing makespan in a flow-shop sequence-dependent group scheduling problem," Journal of Intelligent Manufacturing, Springer, vol. 28(6), pages 1269-1283, August.
    3. Uddin, Muhammad Kutub & Shanker, Kripa, 2002. "Grouping of parts and machines in presence of alternative process routes by genetic algorithm," International Journal of Production Economics, Elsevier, vol. 76(3), pages 219-228, April.
    4. Nikhil Padhye & Piyush Bhardawaj & Kalyanmoy Deb, 2013. "Improving differential evolution through a unified approach," Journal of Global Optimization, Springer, vol. 55(4), pages 771-799, April.
    5. Stefan Helber & Daniel Böhme & Farid Oucherif & Svenja Lagershausen & Steffen Kasper, 2016. "A hierarchical facility layout planning approach for large and complex hospitals," Flexible Services and Manufacturing Journal, Springer, vol. 28(1), pages 5-29, June.
    6. Ignacio Eguia & Jose Carlos Molina & Sebastian Lozano & Jesus Racero, 2017. "Cell design and multi-period machine loading in cellular reconfigurable manufacturing systems with alternative routing," International Journal of Production Research, Taylor & Francis Journals, vol. 55(10), pages 2775-2790, May.
    7. Chunfeng Liu & Jufeng Wang & Joseph Y.-T. Leung & Kai Li, 2016. "Solving cell formation and task scheduling in cellular manufacturing system by discrete bacteria foraging algorithm," International Journal of Production Research, Taylor & Francis Journals, vol. 54(3), pages 923-944, February.
    8. Rossi, Andrea, 2014. "Flexible job shop scheduling with sequence-dependent setup and transportation times by ant colony with reinforced pheromone relationships," International Journal of Production Economics, Elsevier, vol. 153(C), pages 253-267.
    9. Liu, Ying & Dong, Haibo & Lohse, Niels & Petrovic, Sanja, 2016. "A multi-objective genetic algorithm for optimisation of energy consumption and shop floor production performance," International Journal of Production Economics, Elsevier, vol. 179(C), pages 259-272.
    10. Hong-Sen Yan & Xiao-Qin Wan & Fu-Li Xiong, 2015. "Integrated production planning and scheduling for a mixed batch job-shop based on alternant iterative genetic algorithm," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(8), pages 1250-1258, August.
    11. Li, Guo & Liu, Mengqi & Sethi, Suresh P. & Xu, Dehua, 2017. "Parallel-machine scheduling with machine-dependent maintenance periodic recycles," International Journal of Production Economics, Elsevier, vol. 186(C), pages 1-7.
    12. Solimanpur, Maghsud & Elmi, Atabak, 2013. "A tabu search approach for cell scheduling problem with makespan criterion," International Journal of Production Economics, Elsevier, vol. 141(2), pages 639-645.
    13. Solimanpur, M. & Vrat, Prem & Shankar, Ravi, 2004. "A heuristic to minimize makespan of cell scheduling problem," International Journal of Production Economics, Elsevier, vol. 88(3), pages 231-241, April.
    14. Aidin Delgoshaei & Mohd Khairol Anuar Ariffin & Ahad Ali, 2017. "A multi-period scheduling method for trading-off between skilled-workers allocation and outsource service usage in dynamic CMS," International Journal of Production Research, Taylor & Francis Journals, vol. 55(4), pages 997-1039, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ming-Liang Li, 2021. "Standardizing Components and Rotating Workers Using GT-Based Algorithm—A Case Study," Sustainability, MDPI, vol. 13(14), pages 1-17, July.
    2. Li, Guo & Li, Na & Sambandam, Narayanasamy & Sethi, Suresh P. & Zhang, Faping, 2018. "Flow shop scheduling with jobs arriving at different times," International Journal of Production Economics, Elsevier, vol. 206(C), pages 250-260.
    3. Wieslaw Kubiak & Yanling Feng & Guo Li & Suresh P. Sethi & Chelliah Sriskandarajah, 2020. "Efficient algorithms for flexible job shop scheduling with parallel machines," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(4), pages 272-288, June.
    4. Khaled Alhamad & Yousuf Alkhezi & M. F. Alhajri, 2022. "Nonlinear Integer Programming for Solving Preventive Maintenance Scheduling Problem for Cogeneration Plants with Production," Sustainability, MDPI, vol. 15(1), pages 1-18, December.
    5. Jose Joaquin del Pozo-Antúnez & Francisco Fernández-Navarro & Horacio Molina-Sánchez & Antonio Ariza-Montes & Mariano Carbonero-Ruz, 2021. "The Machine-Part Cell Formation Problem with Non-Binary Values: A MILP Model and a Case of Study in the Accounting Profession," Mathematics, MDPI, vol. 9(15), pages 1-16, July.
    6. Mohammadi, Mehrdad & Jula, Payman & Tavakkoli-Moghaddam, Reza, 2019. "Reliable single-allocation hub location problem with disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 123(C), pages 90-120.
    7. Hosseini, Amir & Otto, Alena & Pesch, Erwin, 2024. "Scheduling in manufacturing with transportation: Classification and solution techniques," European Journal of Operational Research, Elsevier, vol. 315(3), pages 821-843.

    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. Shuaipeng Yuan & Tieke Li & Bailin Wang, 2021. "A discrete differential evolution algorithm for flow shop group scheduling problem with sequence-dependent setup and transportation times," Journal of Intelligent Manufacturing, Springer, vol. 32(2), pages 427-439, February.
    2. Zhuang Huang & Jianjun Yang, 2020. "Scheduling Optimization in Flowline Manufacturing Cell Considering Intercell Movement with Harmony Search Approach," Mathematics, MDPI, vol. 8(12), pages 1-21, December.
    3. Wieslaw Kubiak & Yanling Feng & Guo Li & Suresh P. Sethi & Chelliah Sriskandarajah, 2020. "Efficient algorithms for flexible job shop scheduling with parallel machines," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(4), pages 272-288, June.
    4. Iqbal, Asif & Al-Ghamdi, Khalid A., 2018. "Energy-efficient cellular manufacturing system: Eco-friendly revamping of machine shop configuration," Energy, Elsevier, vol. 163(C), pages 863-872.
    5. Dung-Ying Lin & Tzu-Yun Huang, 2021. "A Hybrid Metaheuristic for the Unrelated Parallel Machine Scheduling Problem," Mathematics, MDPI, vol. 9(7), pages 1-20, April.
    6. Shastitko, Anastasia (Шаститко, Анастасия), 2018. "Application of the Conclusions of the Behavioral Economy to the Behavior of Civil Servants: Methodological Aspects [Применение Выводов Поведенческой Экономики К Поведению Государственных Служащих: ," Working Papers 031823, Russian Presidential Academy of National Economy and Public Administration.
    7. Xiaoyan Li & Xuedong Liang & Zhi Li, 2023. "The Strategy of Strengthening Efficiency and Environmental Performance of Product Changeover in the Multiproduct Production System," SAGE Open, , vol. 13(3), pages 21582440231, September.
    8. Ali Derakhshan Asl & Kuan Yew Wong & Manoj Kumar Tiwari, 2016. "Unequal-area stochastic facility layout problems: solutions using improved covariance matrix adaptation evolution strategy, particle swarm optimisation, and genetic algorithm," International Journal of Production Research, Taylor & Francis Journals, vol. 54(3), pages 799-823, February.
    9. Dongni Li & Xianwen Meng & Miao Li & Yunna Tian, 2016. "An ACO-based intercell scheduling approach for job shop cells with multiple single processing machines and one batch processing machine," Journal of Intelligent Manufacturing, Springer, vol. 27(2), pages 283-296, April.
    10. Solimanpur, M. & Vrat, Prem & Shankar, Ravi, 2004. "A heuristic to minimize makespan of cell scheduling problem," International Journal of Production Economics, Elsevier, vol. 88(3), pages 231-241, April.
    11. Hajo Terbrack & Thorsten Claus & Frank Herrmann, 2021. "Energy-Oriented Production Planning in Industry: A Systematic Literature Review and Classification Scheme," Sustainability, MDPI, vol. 13(23), pages 1-32, December.
    12. Alexander Hübner & Heinrich Kuhn & Manuel Walther, 2018. "Combining clinical departments and wards in maximum-care hospitals," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(3), pages 679-709, July.
    13. Mariem Besbes & Marc Zolghadri & Roberta Costa Affonso & Faouzi Masmoudi & Mohamed Haddar, 2020. "A methodology for solving facility layout problem considering barriers: genetic algorithm coupled with A* search," Journal of Intelligent Manufacturing, Springer, vol. 31(3), pages 615-640, March.
    14. Weiwei Cui & Biao Lu, 2020. "A Bi-Objective Approach to Minimize Makespan and Energy Consumption in Flow Shops with Peak Demand Constraint," Sustainability, MDPI, vol. 12(10), pages 1-22, May.
    15. Liang Tang & Zhihong Jin & Xuwei Qin & Ke Jing, 2019. "Supply chain scheduling in a collaborative manufacturing mode: model construction and algorithm design," Annals of Operations Research, Springer, vol. 275(2), pages 685-714, April.
    16. Konstantinos S. Boulas & Georgios D. Dounias & Chrissoleon T. Papadopoulos, 2023. "A hybrid evolutionary algorithm approach for estimating the throughput of short reliable approximately balanced production lines," Journal of Intelligent Manufacturing, Springer, vol. 34(2), pages 823-852, February.
    17. Hanane Krim & Rachid Benmansour & David Duvivier & Daoud Aït-Kadi & Said Hanafi, 2020. "Heuristics for the single machine weighted sum of completion times scheduling problem with periodic maintenance," Computational Optimization and Applications, Springer, vol. 75(1), pages 291-320, January.
    18. Jonatas B. C. Chagas & Julian Blank & Markus Wagner & Marcone J. F. Souza & Kalyanmoy Deb, 2021. "A non-dominated sorting based customized random-key genetic algorithm for the bi-objective traveling thief problem," Journal of Heuristics, Springer, vol. 27(3), pages 267-301, June.
    19. Wu, Lingxiao & Wang, Shuaian, 2018. "Exact and heuristic methods to solve the parallel machine scheduling problem with multi-processor tasks," International Journal of Production Economics, Elsevier, vol. 201(C), pages 26-40.
    20. Wichmann, Matthias Gerhard & Johannes, Christoph & Spengler, Thomas Stefan, 2019. "Energy-oriented Lot-Sizing and Scheduling considering energy storages," International Journal of Production Economics, Elsevier, vol. 216(C), pages 204-214.

    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:eee:proeco:v:196:y:2018:i:c:p:269-283. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijpe .

    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.