Handling constrained many-objective optimization problems via problem transformation

• Main Authors: Jiao, Ruwang, Zeng, Sanyou, Li, Changhe, Yang, Shengxiang, Ong, Yew-Soon
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2022
• Subjects: Engineering::Computer science and engineering; Constrained Optimization; Evolutionary Computation
• Online Access: https://hdl.handle.net/10356/159938
• Institution: Nanyang Technological University

Objectives optimization and constraints satisfaction are two equally important goals to solve constrained many-objective optimization problems (CMaOPs). However, most existing studies for CMaOPs can be classified as feasibility-driven-constrained many-objective evolutionary algorithms (CMaOEAs), and...