Multi-objective configuration optimization of modularized product based on NSGA-II

Method based on the fuzzy evaluation theories and the least squares approximation was advanced to construct configuration optimization mathematical model. Objective functions of the model were performance, cost and term based on modular architecture of product family. Consequently, an improved Non-dominated Sorting Genetic Algorithm (NSGA-II) method was employed to optimize the performance-cost-term multi-objective optimization model of configuration in parallel. As a result, a series of configuration schemes were generated in the form of Pareto optimal set to satisfy individualized customers' demands on the performance, cost and term of product. Finally, an instance related to the project which was applied in the machine industry was given to prove the method's feasibility and validity.