Competitive Parallel Animated Oat Optimization Algorithm

Libin Fu, Shu-Chuan Chu, Jeng-Shyang Pan

Keywords: Animated Oat Optimization, Competitive Parallel, Communication Strategy, Incentive Mechanism

TL;DR: Proposing New Information Communication Strategies and Intra-Group Competition Strategies to Improve the Animated Oat Optimization Algorithm.

Abstract: This paper presents an enhanced version of the Animated Oat Optimization (AOO) algorithm, a novel evolutionary metaheuristic inspired by the rolling and propagation mechanisms of oat seeds in humid environments. To improve its performance, we integrate a parallel co-evolutionary framework with novel communication strategies to facilitate collaboration among subpopulations. Furthermore, a competitive strategy with an incentive mechanism is introduced to promote the evolution of high-quality solutions while reducing computational cost. The proposed algorithm, termed the Competitive Parallel Animated Oat Optimization (CPAOO), is evaluated on the CEC 2017 benchmark suite. Experimental results confirm that CPAOO achieves superior performance compared to several state-of-the-art evolutionary algorithms.

Submission Number: 80