Bi-Level Coordinated Configuration Optimization for Product-Service System Modular Design

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@Article{Li:2017:ieeeTSMC,

• author = "Hao Li and Yangjian Ji and Liang Chen and Roger Jianxin Jiao",
• journal = "IEEE Transactions on Systems, Man, and Cybernetics: Systems",
• title = "Bi-Level Coordinated Configuration Optimization for Product-Service System Modular Design",
• year = "2017",
• volume = "47",
• number = "3",
• pages = "537--554",
• abstract = "Product-service systems (PSSs) deploy a selection of products and services in order to cope with diverse markets, so as to achieve a higher profit than would be possible by offering physical products alone. Modular design inherently contributes to the sustainability performance of PSS by material and resource reuse through the configuration of physical product and service modules. PSS configuration design is enacted through service configuration in line with product configuration; this entails two separate yet coordinated optimization problems, enabling customer satisfaction through service configuration and manufacturers sales profits through product configuration, respectively. Traditional multiobjective optimization approaches assume that the conflicting goals between customers and manufacturers can be aggregated into one single objective function through cooperative protocols, such as a weighted sum; in practice, this scarcely holds true. Consistent with game-theory decision-making, it is necessary to leverage the concerns of customers and manufacturers within a coherent framework of equilibrium solutions. This paper proposes a bi-level coordinated optimization framework to support PSS configuration design. An upper-level optimization problem is formulated for service configuration to act as a leader in the achievement of customer satisfaction, and a lower-level optimization problem is formulated for product configuration to act as a follower in an effort to enhance sales profits. Coordination between the upper and lower levels coincides with the tradeoffs underlying the conflicting goals that exist between customers and manufacturers. A constrained genetic algorithm is developed to solve the bi-level optimization model, and a case study of transformer PSS configuration design is reported to illustrate the feasibility and potential of bi-level coordinated configuration.",
• keywords = "genetic algorithms, genetic programming, Bi-level programming, configuration design optimization, modular design, product-service systems (PSSs)",
• DOI = "doi:10.1109/TSMC.2015.2507407",
• ISSN = "2168-2216",
• month = mar,
• notes = "Also known as \cite{7364287}",

}

Genetic Programming entries for Hao Li Yangjian Ji Liang Chen Roger Jianxin Jiao

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