A new approach for customer-driven product configuration optimization is proposed. Configuration space against the defects of product family model is constructed for targeting diversity of customer needs and conjoint analysis is applied to decompose the customer preference into the utility of different product attributes. Subsequently

a mathematic model to maximize the ratio between the overall utility and cost from both customers and manufacturers perspectives is formulated

and a genetic algorithm is adopted to solve this combinatory optimization problem. A case study of notebook computer is then reported to illustrate the validity of the proposed method and associated algorithms

which demonstrates that the proposed approach provides an effective means for assemble-to-order manufacturing enterprises to acquire the customer-satisfied configuration solution.