FindingsThe achieved numerical results empirically prove the superiority of the proposed method to state-of-the-art counterparts in the most test problems of a known artificial benchmark.Originality/valueThis paper provides a new interpretation and important insights into the many-objective optimization ...
This paper presents a meta-objective optimization approach, called Bi-Goal Evolution (BiGE), to deal with many-objective optimization problems. Inspired by two observations: 1) the conflict between proximity and diversity requirements is aggravated with the increase of the number of objectives and 2...
Kang, Z.et al.(2007). A New Evolutionary Decision Theory for Many-Objective Optimization Problems. In: Kang, L., Liu, Y., Zeng, S. (eds) Advances in Computation and Intelligence. ISICA 2007. Lecture Notes in Computer Science, vol 4683. Springer, Berlin, Heidelberg. https://doi.org/1...
Liu. Bi-goal evolution for many-objective opti- mization problems. Artificial Intelligence, 228:45-65, 2015.M. Li, S. Yang, and X. Liu, "Bi-goal evolution for many-objective optimization problems," Artificial Intelligence, vol. 228, pp. 45-65, 2015....
Many-objective optimizationMOON2MOON2RPairwise comparisonAHPNeural networkA multi-objective optimization (MUOP) method that supports agile and flexible decision making to be able to handle complex and diverse decision environments has been in high demand. This study......
When solving many-objective optimization problems, evolutionary algorithms do not differentiate between solutions due to the large number of objectives inv... D Zouache,F Ben Abdelaziz - 《Annals of Operations Research》 被引量: 0发表: 0年 An exact -constraint method for bi-objective combinatorial...
Evolutionary algorithms have shown their promise in coping with many-objective optimization problems. However, the strategies of balancing convergence and diversity and the effectiveness of handling problems with irregular Pareto fronts (PFs) are still far from perfect. To address these issues, this ...
problems, and the presented concepts may also be helpful for other types of quality indicators to be integrated in the optimization process. II. A BRIEF REVIEW OF HYPERVOLUME-RELATED RESEARCH The hypervolume indicator was originally proposed and ...
Many-objective optimization problems(MaOPs) are the most challenging problems among multi-objective optimization problems (MOPs). Objective reduction method has become one of the most important technique for MaOPs which can alleviate the difficulties of selection pressure, computational cost and the human...
The experimental results show that the proposed method can work well on most instances considered in this study, demonstrating that it is very competitive for solving many-objective optimization problems.doi:10.1007/978-3-030-23712-7_28Huaxian Pan...