A Many-Objective Evolutionary Algorithm With Enhanced Mating and Environmental Selections

• Published in: IEEE transactions on evolutionary computation Vol. 19; no. 4; pp. 592 - 605
• Main Authors: Jixiang Cheng, Yen, Gary G., Gexiang Zhang
• Format: Journal Article
• Language: English
• Published: IEEE 01.08.2015
• Subjects: Algorithm design and analysis; Convergence; directional diversity; Evolutionary computation; favorable convergence; Maintenance engineering; many- objective evolutionary algorithm; Many-objective optimization problem; Optimization; Sociology; Statistics; many-objective optimization problem (MaOP); many-objective evolutionary algorithm (MaOEA); Directional diversity (DD); favorable convergence (FC)

Multiobjective evolutionary algorithms have become prevalent and efficient approaches for solving multiobjective optimization problems. However, their performances deteriorate severely when handling many-objective optimization problems (MaOPs) due to the loss of selection pressure to drive the searc...