Affiliations: [a] Department of Industrial & Systems Engineering, National University of Singapore, Singapore | [b] State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, China | [c] Department of Supply Chain Management, W. P. Carey School of Business, Arizona State University, Arizona, USA
Correspondence:
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Corresponding author. Yu Guodong, Department of Industrial & Systems Engineering, National University of Singapore, Singapore. Tel.: +8613132397756; Fax: +23 65106606; E-mail: yuguodong@cqu.edu.cn.
Abstract: Changing customer requirements always poses a great challenge to designers in complex product design. Due to the complicated coupling relations between components, it is difficult to improve the efficiency of product reconfiguration. Therefore, this paper proposes a joint optimization model of complex product variant design responding to customer requirement changes. Based on synthesizing the advantages and deficiencies of “Scaled-based” and “Module-based”, a UB-BU hybrid approach is developed to improve the search efficiency and reduce conflicts. Then, a joint complex product variant design bi-level optimization to maximize customer satisfaction and minimum cost is established. As a solution, the genetic algorithm embedded double iteration comparison rules (GA-DICR) is developed based on canonical genetic algorithm. Finally, the method and model are proved to be effective in the Clutch variant design. The results can provide way of allowing the decision-makers to respond rapidly to customer rudiments changes request.
