Researchers at Fuzhou University Report New Data on Mathematics (Improved Optimal Foraging Algorithm for Global Optimization).

Researchers at Fuzhou University in the People's Republic of China have developed an improved optimal foraging algorithm (OFA) for global optimization. The OFA is a swarm-based algorithm inspired by animal behavioral ecology theory. The researchers introduced a new algorithm called QOS-OFA, which incorporates quasi-opposition-based learning, an efficient cosine-based scale factor, and a search strategy with social behavior. The QOS-OFA was compared to seven other meta-heuristic algorithms and performed better on most test problems. This research has been peer-reviewed and published in the journal Computing. [Extracted from the article]