An improved multi-objective optimization method based on adaptive mutation particle swarm optimization and fuzzy statistics algorithm

ABSTRACT

This paper proposes an adaptive mutation particle swarm optimization (AMPSO) to realize multi-objective optimization design method through scale-based product platform theory model. The Pareto-optimal solution was obtained via AMPSO, then the fuzzy statistics algorithm is presented to extract the optimal solution of multi-objective optimization problem. The Multi-objective Optimization Method was carried out in two stages. In the first stage, each product is optimized independently via AMPSO and the product platform constant parameter and its value is obtained according to the change ratio of design variables; In the second stage, the scaling variables of each product are solved via AMPSO based on the optimization objectives improving the performance in constraint of restrictions and the best compromise solution is extracted based on fuzzy statistics algorithm.

KEYWORDS:

• Multi-objective optimization
• flexibility design
• scaling variables
• fuzzy statistics algorithm
• AMPSO
• product family

Additional information

Funding

This research is supported by the National Natural Science Foundation of China [Grant number 51675028].