A Multi-Objective Evolutionary Algorithm Model for Product Form Design Based on Improved SPEA2

• Main Authors: Zeng Wang, Weidong Liu, Minglang Yang, Dongji Han
• Format: Article
• Language: English
• Published: MDPI AG 2019-07-01
• Series: Applied Sciences
• Subjects: product form design; Kansei engineering; multi-objective evolutionary algorithm; improved SPEA2; elliptic Fourier analysis (EFA); entropy-TOPSIS
• Online Access: https://www.mdpi.com/2076-3417/9/14/2944

As a Kansei engineering design expert system, the product form design multi-objective evolutionary algorithm model (PFDMOEAM) contains various methods. Among them, the multi-objective evolutionary algorithm (MOEA) is the key to determine the performance of the model. Due to the deficiency of MOEA, the traditional PFDMOEAM has limited innovation and application value for designers. In this paper, we propose a novel PFDMOEAM with an improved strength Pareto evolutionary algorithm 2 (ISPEA2) as the core and combining the elliptic Fourier analysis (EFA) and the entropy weight and technique for order preference by similarity to ideal solution (entropy-TOPSIS) methods. Based on the improvement of the original operators in SPEA2 and the introduction of a new operator, ISPEA2 outperforms SPEA2 in convergence and diversity simultaneously. The proposed model takes full advantage of this superiority, and further combines the EFA method’s high accuracy and degree of multi-method integration, as well as the entropy-TOPSIS method’s good objectivity and operability, so it has excellent comprehensive performance and innovative application value. The feasibility and effectiveness of the model are verified by a case study of a car form design. The simulation system of the model is developed, and the simulation results demonstrate that the model can provide a universal and effective tool for designers to carry out multi-objective evolutionary design of product form.