A Multi-Objective Optimization Approach to Product Configuration Design with the Consideration of Uncertain Information

• Published in: Applied Mechanics and Materials Vol. 236-237; pp. 1078 - 1084
• Main Authors: Li, Guo Xi, Zhang, Meng, Yan, Yue Hui, Wu, Bao Zhong
• Format: Journal Article
• Language: English
• Published: Zurich Trans Tech Publications Ltd 01.11.2012
• Subjects: NSGA-II; Uncertain Information; Configuration Optimization; Multi-Objective; Pareto Optimal Set
• ISBN: 3037855312; 9783037855317
• ISSN: 1660-9336; 1662-7482; 1662-7482
• DOI: 10.4028/www.scientific.net/AMM.236-237.1078

The current product configuration methods can only be applied to the situation when the configuration information is specific or fuzzy. In order to address this problem, a new multi-objective optimization approach to configuration design with the consideration of several types of uncertain information was proposed. The uncertain configuration information was uniformly described with interval numbers. Targeting on optimizing the performance, cost and term of configured products, three mathematical models was established, and some adaptations were made to these models according to the interval number. A multi-objective optimization model was generated by integrating the three models. The non-dominated sorting genetic algorithm II was used to solve the model and a Pareto optimal set of product configuration schemes was obtained. A general optimum selection method was put forward based on the fuzzy set theory, and the optimization sequence of the Pareto solutions can be founded using the method. The proposed approach can effectively deal with the problem of product configuration optimization under uncertain information.