A Two-Archive Algorithm with Interactive Mechanism for Many-Objective Optimization.

Autor: Liu, Shuren, Li, Shuping, Li, Changchun, Cai, Changning, Cheng, Guojian
Předmět:
Zdroj: Mathematical Problems in Engineering; 12/19/2023, p1-12, 12p
Abstrakt: This paper proposes an interactive two-archive method to solve many-objective optimization problems. Two updating strategies based on the aggregation-based framework are presented and incorporated into a two-archive framework. In addition, we further extend this method by introducing an interactive mechanism in which evolutionary information is passed from the diversity archive to the convergence archive. Given the requirement to balance convergence and diversity, a mating selection method is proposed to regulate the evolutionary speed of these two archives collaboratively. The proposed algorithm has been tested extensively on several problems with different peer algorithms to validate its effectiveness. The results show that the proposed method can outperform several state-of-the-art evolutionary algorithms for handling many-objective optimization. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index
Externí odkaz:
Nepřihlášeným uživatelům se plný text nezobrazuje