The Colony Predation Algorithm

Abstract This paper proposes a new stochastic optimizer called the Colony Predation Algorithm (CPA) based on corporate predation of animals in nature. CPA utilizes mathematical mapping following strategies used by animal hunting groups, such as dispersing prey, encircling supporting most likely successful hunter, and seeking another target. Moreover, proposed introduces features unique model that uses success rate to adjust strategy simulate animals’ selective abandonment behavior. also presents way deal with cross-border situations, whereby optimal position value situation replaces improve algorithm’s exploitation ability. The was compared state-of-the-art metaheuristics comprehensive set benchmark functions for performance verification five classical engineering design problems evaluate efficacy optimizing problems. results show algorithm exhibits competitive, superior different search landscapes over other algorithms. source code will be publicly available after publication.