IDEAS home Printed from https://ideas.repec.org/a/spr/joinma/v35y2024i7d10.1007_s10845-023-02191-4.html
   My bibliography  Save this article

Evolutionary algorithms for a simheuristic optimization of the product-service system design

Author

Listed:
  • Henri Meeß

    (Fraunhofer Institute for Transportation and Infrastructure Systems IVI)

  • Michael Herzog

    (Ruhr-Universität Bochum
    Ruhr-Universität Bochum)

  • Enes Alp

    (Ruhr-Universität Bochum)

  • Bernd Kuhlenkötter

    (Ruhr-Universität Bochum
    Ruhr-Universität Bochum)

Abstract

Offering Product-Service Systems (PSS) becomes an established strategy for companies to increase the provided customer value and ensure their competitiveness. Designing PSS business models, however, remains a major challenge. One reason for this is the fact that PSS business models are characterized by a long-term nature. Decisions made in the development phase must take into account possible scenarios in the operational phase. Risks must already be anticipated in this phase and mitigated with appropriate measures. Another reason for the design phase being a major challenge is the size of the solution space for a possible business model. Developers are faced with a multitude of possible business models and have the challenge of selecting the best one. In this article, a simheuristic optimization approach is developed to test and evaluate PSS business models in the design phase in order to select the best business model configuration beforehand. For optimization, a proprietary evolutionary algorithm is developed and tested. The results validate the suitability of the approach for the design phase and the quality of the algorithm for achieving good results. This could even be transferred to already established PSS.

Suggested Citation

  • Henri Meeß & Michael Herzog & Enes Alp & Bernd Kuhlenkötter, 2024. "Evolutionary algorithms for a simheuristic optimization of the product-service system design," Journal of Intelligent Manufacturing, Springer, vol. 35(7), pages 3235-3257, October.
    • Handle: RePEc:spr:joinma:v:35:y:2024:i:7:d:10.1007_s10845-023-02191-4
    DOI: 10.1007/s10845-023-02191-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10845-023-02191-4
    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/s10845-023-02191-4?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. Chih, Mingchang, 2023. "Stochastic stability analysis of particle swarm optimization with pseudo random number assignment strategy," European Journal of Operational Research, Elsevier, vol. 305(2), pages 562-593.
    2. Li, Ai Qiang & Kumar, Maneesh & Claes, Björn & Found, Pauline, 2020. "The state-of-the-art of the theory on Product-Service Systems," International Journal of Production Economics, Elsevier, vol. 222(C).
    3. Javier Panadero & Angel A. Juan & Christopher Bayliss & Christine Currie, 2020. "Maximising reward from a team of surveillance drones: a simheuristic approach to the stochastic team orienteering problem," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 14(4), pages 485-516.
    4. 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.
    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. 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.
    2. Omer Ozkan & Sezgin Kilic, 2023. "UAV routing by simulation-based optimization approaches for forest fire risk mitigation," Annals of Operations Research, Springer, vol. 320(2), pages 937-973, January.
    3. 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.
    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. Lam, Chiou-Peng & Masek, Martin & Kelly, Luke & Papasimeon, Michael & Benke, Lyndon, 2019. "A simheuristic approach for evolving agent behaviour in the exploration for novel combat tactics," Operations Research Perspectives, Elsevier, vol. 6(C).
    6. Poorya Ghafoorpoor Yazdi & Aydin Azizi & Majid Hashemipour, 2019. "A Hybrid Methodology for Validation of Optimization Solutions Effects on Manufacturing Sustainability with Time Study and Simulation Approach for SMEs," Sustainability, MDPI, vol. 11(5), pages 1-26, March.
    7. 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.
    8. Mosch, Philipp & Schweikl, Stefan & Obermaier, Robert, 2021. "Trapped in the supply chain? Digital servitization strategies and power relations in the case of an industrial technology supplier," International Journal of Production Economics, Elsevier, vol. 236(C).
    9. 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.
    10. Garside, Annisa Kesy & Ahmad, Robiah & Muhtazaruddin, Mohd Nabil Bin, 2024. "A recent review of solution approaches for green vehicle routing problem and its variants," Operations Research Perspectives, Elsevier, vol. 12(C).
    11. Gabriel Mauricio Zambrano-Rey & Eliana María González-Neira & Gabriel Fernando Forero-Ortiz & María José Ocampo-Monsalve & Andrea Rivera-Torres, 2024. "Minimizing the expected maximum lateness for a job shop subject to stochastic machine breakdowns," Annals of Operations Research, Springer, vol. 338(1), pages 801-833, July.
    12. Manuel Chica & Joaquín Bautista & Jesica de Armas, 2019. "Benefits of robust multiobjective optimization for flexible automotive assembly line balancing," Flexible Services and Manufacturing Journal, Springer, vol. 31(1), pages 75-103, March.
    13. Shiri, Davood & Akbari, Vahid & Hassanzadeh, Ali, 2024. "The Capacitated Team Orienteering Problem: An online optimization framework with predictions of unknown accuracy," Transportation Research Part B: Methodological, Elsevier, vol. 185(C).
    14. José García & José V. Martí & Víctor Yepes, 2020. "The Buttressed Walls Problem: An Application of a Hybrid Clustering Particle Swarm Optimization Algorithm," Mathematics, MDPI, vol. 8(6), pages 1-22, May.
    15. Wang, Jianzhou & Dong, Yunxuan & Zhang, Kequan & Guo, Zhenhai, 2017. "A numerical model based on prior distribution fuzzy inference and neural networks," Renewable Energy, Elsevier, vol. 112(C), pages 486-497.
    16. Leandro do C. Martins & Rafael D. Tordecilla & Juliana Castaneda & Angel A. Juan & Javier Faulin, 2021. "Electric Vehicle Routing, Arc Routing, and Team Orienteering Problems in Sustainable Transportation," Energies, MDPI, vol. 14(16), pages 1-30, August.
    17. Elisa Negri & Vibhor Pandhare & Laura Cattaneo & Jaskaran Singh & Marco Macchi & Jay Lee, 2021. "Field-synchronized Digital Twin framework for production scheduling with uncertainty," Journal of Intelligent Manufacturing, Springer, vol. 32(4), pages 1207-1228, April.
    18. Li, Huashan & Pournader, Mehrdokht & Fahimnia, Behnam, 2022. "Servitization and organizational resilience of manufacturing firms: Evidence from the COVID-19 outbreak," International Journal of Production Economics, Elsevier, vol. 250(C).
    19. José García & Paola Moraga & Matias Valenzuela & Hernan Pinto, 2020. "A db-Scan Hybrid Algorithm: An Application to the Multidimensional Knapsack Problem," Mathematics, MDPI, vol. 8(4), pages 1-22, April.
    20. José Lemus-Romani & Marcelo Becerra-Rozas & Broderick Crawford & Ricardo Soto & Felipe Cisternas-Caneo & Emanuel Vega & Mauricio Castillo & Diego Tapia & Gino Astorga & Wenceslao Palma & Carlos Castro, 2021. "A Novel Learning-Based Binarization Scheme Selector for Swarm Algorithms Solving Combinatorial Problems," Mathematics, MDPI, vol. 9(22), pages 1-41, 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:spr:joinma:v:35:y:2024:i:7:d:10.1007_s10845-023-02191-4. 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.