Abstract: In order to resolve the constraints network involving complex coupling relationships in cooperative design process, generalized dynamic constraints satisfaction (GDCS) is studied, and a two-layer combinatorial heuristic algorithm is proposed based on improved particle swarm optimization (PSO) combined with fuzzy matter element analysis (FMEA). The FMEA is used in the first layer to establish the relation-element model of GDCS and transform the multi-objective optimization problems to the single-objective ones; The improved PSO is used in the second layer, on the basis of standard PSO algorithm, the adaptive mutation probability and the response mode of dynamic updating are introduced to improve the adaptability of particles for the dynamic environment, which is intend to make the algorithm to track the latest change of system extremum introduced by dynamic constrains in the process of collaborative design. Finally, a design example verifies the effectiveness of the proposed method. GDCS-oriented combinatorial heuristic algorithm provides a formal and dynamic method to model and solve the constraints network in collaborative product design process.

Key words: Cooperative design, Flexible tracking particle swarm optimization algorithm, Fuzzy matter-element analysis, Generalized dynamic constraint satisfaction