In this work, we present a new multi-objective particle swarm optimization algorithm (PSO) characterized by the use of the geometrization analysis of the particles. The proposed method, called geometry analysis PSO (GAPSO), firstly parameterize the data points of the optimization model of mechatronic system to obtain their parameter values, then one curve or one surface is adopted to fit these points and the tangent value and normal value for each point are acquired, eventually the particles are guided by the use of its derivative value and tangent value to approximate the true Pareto front and get a uniform distribution. Our proposed method is compared with respect to two multi-objective metaheuristics representative of the state-of-the-art in this area. The experiments carried out indicate that GAPSO obtains remarkable results in terms of both accuracy and distribution.

This content is only available via PDF.
You do not currently have access to this content.