Abstract
Configuration is an efficient method for rapid PSS customization. However, the previous service configuration methods may produce a large number of feasible solutions, especially when there are more module instances or fewer configuration constraints. This will increase the burden of service solution screening and reduce the efficiency of service delivery. To solve this problem, Song and Chan (2015) develop a multi-objective optimization model for configuration of the PSS. The optimization model considers service performance, service cost and response time at the same time, and it is solved with non-dominated sorting genetic algorithm II (NSGA II) to obtain a set of optimal configuration solutions. In this way, the manufacturer can flexibly satisfy customer needs with a module-based PSS at lower cost. The PSS configuration optimization model is expected to enhance the customization ability of the service provider, because it can respond to customer requirements timely by providing the customized PSS. The rough TOPSIS approach developed by Song et al. (2013b) can then be used to evaluate and select the proper PSS concept from the configured PSS set.
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Song, W. (2019). Modular Configuration for Customizable PSS. In: Customization-Oriented Design of Product-Service System. Springer, Singapore. https://doi.org/10.1007/978-981-13-0863-5_5
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DOI: https://doi.org/10.1007/978-981-13-0863-5_5
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