IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v340y2024i1d10.1007_s10479-023-05813-5.html
   My bibliography  Save this article

A hybrid method to solve reliability-cost-oriented bi-objective machine configuration problem for a flow shop system

Author

Listed:
  • Cheng-Ta Yeh

    (Fu Jen Catholic University)

  • Louis Cheng-Lu Yeng

    (National Yang Ming Chiao Tung University)

  • Yi-Kuei Lin

    (National Yang Ming Chiao Tung University
    Asia University
    Chaoyang University of Technology
    Graphic Era Deemed to Be University)

  • Yu-Lun Chao

    (National Yang Ming Chiao Tung University)

Abstract

Machine configuration is a crucial strategic decision in designing a flow shop system (FSS) and directly affects its performance. This involves selecting device suppliers and determining the number of machines to be configured. This study addresses a bi-objective optimization problem for an FSS that considers repair actions and aims to determine the most suitable machine configuration that balances the production reliability and purchase cost. A nondominated sorting genetic algorithm II (NSGA-II) is used to determine all the Pareto solutions. The technique for order preference by similarity to an ideal solution is then used to identify a compromise alternative. It is necessary to assess the production reliability of any machine configuration identified by the NSGA-II. The FSS under the machine configuration is modeled as a multistate flow shop network, and Absorbing Markov Chain and Recursive Sum of Disjoint Products are integrated into the NSGA-II for reliability evaluation. The experimental results of solar cell manufacturing demonstrate the applicability of the proposed hybrid method and validate the efficiency of the NSGA-II compared with an improved strength Pareto evolutionary algorithm.

Suggested Citation

  • Cheng-Ta Yeh & Louis Cheng-Lu Yeng & Yi-Kuei Lin & Yu-Lun Chao, 2024. "A hybrid method to solve reliability-cost-oriented bi-objective machine configuration problem for a flow shop system," Annals of Operations Research, Springer, vol. 340(1), pages 643-669, September.
  • Handle: RePEc:spr:annopr:v:340:y:2024:i:1:d:10.1007_s10479-023-05813-5
    DOI: 10.1007/s10479-023-05813-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-023-05813-5
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10479-023-05813-5?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. Tzu-Li Chen & Chen-Yang Cheng & Yi-Han Chou, 2020. "Multi-objective genetic algorithm for energy-efficient hybrid flow shop scheduling with lot streaming," Annals of Operations Research, Springer, vol. 290(1), pages 813-836, July.
    2. G C Hadjinicola, 2010. "Manufacturing costs in serial production systems with rework," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(2), pages 342-351, February.
    3. Md. Shahriar J. Hossain & Bhaba R. Sarker, 2016. "Optimal locations of on-line and off-line rework stations in a serial production system," International Journal of Production Research, Taylor & Francis Journals, vol. 54(12), pages 3603-3621, June.
    4. Zhang, Xinhui & Bard, Jonathan F., 2006. "A multi-period machine assignment problem," European Journal of Operational Research, Elsevier, vol. 170(2), pages 398-415, April.
    5. Cheng-Ta Yeh & Ping-Chen Chang & Chin-Yeu Chen, 2017. "Minimal production level and reliability measurement for a maintainable production system under demand and budget constraints," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 11(4), pages 526-547.
    6. Lin, Yi-Kuei & Yeh, Cheng-Ta, 2012. "Multi-objective optimization for stochastic computer networks using NSGA-II and TOPSIS," European Journal of Operational Research, Elsevier, vol. 218(3), pages 735-746.
    7. Brammer, Janis & Lutz, Bernhard & Neumann, Dirk, 2022. "Permutation flow shop scheduling with multiple lines and demand plans using reinforcement learning," European Journal of Operational Research, Elsevier, vol. 299(1), pages 75-86.
    8. Bowling, Shannon R. & Khasawneh, Mohammad T. & Kaewkuekool, Sittichai & Cho, Byung Rae, 2004. "A Markovian approach to determining optimum process target levels for a multi-stage serial production system," European Journal of Operational Research, Elsevier, vol. 159(3), pages 636-650, December.
    9. Joseph C. Hudson & Kailash C. Kapur, 1985. "Reliability Bounds for Multistate Systems with Multistate Components," Operations Research, INFORMS, vol. 33(1), pages 153-160, February.
    10. Dolgui, Alexandre & Hashemi-Petroodi, S. Ehsan & Kovalev, Sergey & Kovalyov, Mikhail Y., 2021. "Profitability of a multi-model manufacturing line versus multiple dedicated lines," International Journal of Production Economics, Elsevier, vol. 236(C).
    11. Jonathan Oesterle & Lionel Amodeo & Farouk Yalaoui, 2019. "A comparative study of Multi-Objective Algorithms for the Assembly Line Balancing and Equipment Selection Problem under consideration of Product Design Alternatives," Journal of Intelligent Manufacturing, Springer, vol. 30(3), pages 1021-1046, March.
    12. Sarker, Bhaba R. & Jamal, A.M.M. & Mondal, Sanjay, 2008. "Optimal batch sizing in a multi-stage production system with rework consideration," European Journal of Operational Research, Elsevier, vol. 184(3), pages 915-929, February.
    13. Juan, Angel A. & Faulin, Javier & Grasman, Scott E. & Rabe, Markus & Figueira, Gonçalo, 2015. "A review of simheuristics: Extending metaheuristics to deal with stochastic combinatorial optimization problems," Operations Research Perspectives, Elsevier, vol. 2(C), pages 62-72.
    14. Thi-Phuong Nguyen, 2022. "Evaluation of network reliability for stochastic-flow air transportation network considering discounted fares from airlines," Annals of Operations Research, Springer, vol. 311(1), pages 335-355, April.
    15. Yi-Kuei Lin & Shin-Guang Chen, 2022. "Reliability evaluation in terms of flow data mining for multistate networks," Annals of Operations Research, Springer, vol. 311(1), pages 225-237, April.
    16. Yi-Kuei Lin & Ping-Chen Chang, 2015. "Demand satisfaction and decision-making for a PCB manufacturing system with production lines in parallel," International Journal of Production Research, Taylor & Francis Journals, vol. 53(11), pages 3193-3206, June.
    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. Battaïa, Olga & Dolgui, Alexandre, 2022. "Hybridizations in line balancing problems: A comprehensive review on new trends and formulations," International Journal of Production Economics, Elsevier, vol. 250(C).
    2. Noordhoek, Marije & Dullaert, Wout & Lai, David S.W. & de Leeuw, Sander, 2018. "A simulation–optimization approach for a service-constrained multi-echelon distribution network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 292-311.
    3. 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.
    4. Romauch, Martin & Hartl, Richard F., 2017. "Capacity planning for cluster tools in the semiconductor industry," International Journal of Production Economics, Elsevier, vol. 194(C), pages 167-180.
    5. Yeh, Wei-Chang & Bae, Changseok & Huang, Chia-Ling, 2015. "A new cut-based algorithm for the multi-state flow network reliability problem," Reliability Engineering and System Safety, Elsevier, vol. 136(C), pages 1-7.
    6. Lin, Yi-Kuei, 2010. "Calculation of minimal capacity vectors through k minimal paths under budget and time constraints," European Journal of Operational Research, Elsevier, vol. 200(1), pages 160-169, January.
    7. Chang, Ping-Chen, 2024. "A path-based simulation approach for multistate flow network reliability estimation without using boundary points," Reliability Engineering and System Safety, Elsevier, vol. 249(C).
    8. Chen, Chung-Ho & Lai, Min-Tsai, 2007. "Economic manufacturing quantity, optimum process mean, and economic specification limits setting under the rectifying inspection plan," European Journal of Operational Research, Elsevier, vol. 183(1), pages 336-344, November.
    9. Xu, Jiuping & Song, Xiaoling & Wu, Yimin & Zeng, Ziqiang, 2015. "GIS-modelling based coal-fired power plant site identification and selection," Applied Energy, Elsevier, vol. 159(C), pages 520-539.
    10. Yu, Yang & Tang, Jiafu & Gong, Jun & Yin, Yong & Kaku, Ikou, 2014. "Mathematical analysis and solutions for multi-objective line-cell conversion problem," European Journal of Operational Research, Elsevier, vol. 236(2), pages 774-786.
    11. Lin, Yi-Kuei & Yeh, Cheng-Ta, 2011. "Maximal network reliability for a stochastic power transmission network," Reliability Engineering and System Safety, Elsevier, vol. 96(10), pages 1332-1339.
    12. Al-Salamah, Muhammad, 2019. "Economic production quantity in an imperfect manufacturing process with synchronous and asynchronous flexible rework rates," Operations Research Perspectives, Elsevier, vol. 6(C).
    13. José García & Victor Yepes & José V. Martí, 2020. "A Hybrid k-Means Cuckoo Search Algorithm Applied to the Counterfort Retaining Walls Problem," Mathematics, MDPI, vol. 8(4), pages 1-22, April.
    14. Mohammad Peyman & Pedro J. Copado & Rafael D. Tordecilla & Leandro do C. Martins & Fatos Xhafa & Angel A. Juan, 2021. "Edge Computing and IoT Analytics for Agile Optimization in Intelligent Transportation Systems," Energies, MDPI, vol. 14(19), pages 1-26, October.
    15. Andrés Martínez-Reyes & Carlos L. Quintero-Araújo & Elyn L. Solano-Charris, 2021. "Supplying Personal Protective Equipment to Intensive Care Units during the COVID-19 Outbreak in Colombia. A Simheuristic Approach Based on the Location-Routing Problem," Sustainability, MDPI, vol. 13(14), pages 1-16, July.
    16. Yi-Kuei Lin & Lance Fiondella & Ping-Chen Chang, 2022. "Reliability of time-constrained multi-state network susceptible to correlated component faults," Annals of Operations Research, Springer, vol. 311(1), pages 239-254, April.
    17. Mitali Sarkar & Li Pan & Bikash Koli Dey & Biswajit Sarkar, 2020. "Does the Autonomation Policy Really Help in a Smart Production System for Controlling Defective Production?," Mathematics, MDPI, vol. 8(7), pages 1-21, July.
    18. Li, Yaping & Xia, Tangbin & Chen, Zhen & Pan, Ershun, 2023. "Multiple degradation-driven preventive maintenance policy for serial-parallel multi-station manufacturing systems," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    19. Máximo Méndez & Mariano Frutos & Fabio Miguel & Ricardo Aguasca-Colomo, 2020. "TOPSIS Decision on Approximate Pareto Fronts by Using Evolutionary Algorithms: Application to an Engineering Design Problem," Mathematics, MDPI, vol. 8(11), pages 1-27, November.
    20. Huang, Ding-Hsiang, 2024. "An algorithm to generate all d-lower boundary points for a stochastic flow network using dynamic flow constraints," Reliability Engineering and System Safety, Elsevier, vol. 249(C).

    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:spr:annopr:v:340:y:2024:i:1:d:10.1007_s10479-023-05813-5. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.