This research addresses the issues to identify the optimal product configuration and its parameters based on the requirements of customers on performance and costs of products in one-of-a-kind production (OKP) environment. In this work, variations of product configurations and parameters in an OKP product family are modeled by an AND-OR tree and parameters of the nodes in this tree. Different product configurations with different parameters are evaluated by performance and cost measures. These evaluation measures are converted into comparable customer satisfaction indices using the non-linear relations between the evaluation measures and the customer satisfaction indices. The optimal product configuration and its parameters with the maximum overall customer satisfaction index are identified by genetic programming and constrained optimization.

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