Comparison between MOEA/D and NSGA-III on a set of many and multi-objective benchmark problems with challenging difficulties

• Main Authors: Li, Hui, Deb, Kalyanmoy, Zhang, Qingfu, Suganthan, Ponnuthurai Nagaratnam, Chen, Lei
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2021
• Subjects: Engineering::Electrical and electronic engineering; Many-objective Optimization; Evolutionary Algorithms
• Online Access: https://hdl.handle.net/10356/151704
• Institution: Nanyang Technological University

Currently, evolutionary multiobjective optimization (EMO) algorithms have been successfully used to find a good approximation of many-objective optimization problems (MaOPs). To measure the performance of EMO algorithms, many benchmark multiobjective test problems have been constructed. Among them,...