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

Henri Meeß (), Michael Herzog (), Enes Alp () and Bernd Kuhlenkötter ()
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Henri Meeß: Fraunhofer Institute for Transportation and Infrastructure Systems IVI
Michael Herzog: Ruhr-Universität Bochum
Enes Alp: Ruhr-Universität Bochum
Bernd Kuhlenkötter: Ruhr-Universität Bochum

Journal of Intelligent Manufacturing, 2024, vol. 35, issue 7, No 13, 3235-3257

Abstract: 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.

Keywords: Product-Service Systems (PSS); Business model prototyping; Simheuristics; Evolutionary algorithms; Metaheuristic optimization (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10845-023-02191-4

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