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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 \u201cScaled-based\u201d and \u201cModule-based\u201d, 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.<\/jats:p>","DOI":"10.3233\/ifs-151764","type":"journal-article","created":{"date-parts":[[2016,1,15]],"date-time":"2016-01-15T12:23:17Z","timestamp":1452860597000},"page":"397-408","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":9,"title":["Joint optimization of complex product variant design responding to customer requirement changes"],"prefix":"10.1177","volume":"30","author":[{"given":"Yu","family":"Guodong","sequence":"first","affiliation":[{"name":"Department of Industrial &amp; Systems Engineering, National University of Singapore, Singapore"}]},{"given":"Yang","family":"Yu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, China"}]},{"given":"Liu","family":"Aijun","sequence":"additional","affiliation":[{"name":"Department of Supply Chain Management, W. 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