User-oriented product conceptual design of intelligent instrument based on genetic algorithm

Product conceptual design has been recognized as a critical decision. It aims at the selection of modules to offer near-optimal solutions of product design scheme and assist designers in product decision-making. It constitutes a combinatorial optimization problem. Conventional enumeration-based optimization techniques become inhibitive given that the number of possible combinations may be enormous. Genetic algorithms have been proven to excel in solving combinatorial optimization problems. This paper develops a genetic algorithm for solving the product conceptual design problem of intelligent instrument more effectively. A binary encoding scheme is presented to represent compositional model of modules. In order to avoid prematurity and convergence out of optimized point for genetic algorithm, a fitness normalization formula is introduced.