An Artificial Intelligence approach for the multicriteria optimization in mechatronic products design

This study is related to the integration of Artificial Intelligence approaches in the optimization of mechatronic products design. The purpose is to help designers to choose design parameters according to technical specifications and customers needs. Because of the high number of parameters and possible combinations, a heuristic based approach is investigated for optimization activity when the task is a multiple objective combinatorial one and when the criteria to be optimized cannot be weighted or ordered. A Hybrid Search (HS) algorithm based on some metaheuristic mechanisms is proposed for optimization without resuming the multiple objectives to a single one. The specified algorithm derives the best (not dominated) solution set: the Pareto front, from the set of acceptable solutions defined by the design parameters, and is quite faster compared to exhaustive methods. Self-organizing Maps are then used to analyze the obtained fronts. Our approach is fully illustrated in the case of the design of a 2-Degrees Of Freedom robot.