Cockroach Swarm Optimization Using A Neighborhood-Based Strategy

The original Cockroach Swarm Optimization (CSO) algorithm suffers from the problems of slow or premature convergence. This paper described a new cockroach-inspired algorithm, which is called CSO with Global and Local neighborhoods (CSOGL). In CSOGL, two kinds of neighborhood models are designed, in order to increase the diversity of promising solution. Based on above two neighborhood models, two kinds of novel chase-swarming behaviors are proposed and applied to CSOGL. Moreover, this paper also provides a formal convergence proof for the CSOGL algorithm. The comparison results show that the CSOGL algorithm outperform the existing cockroach-inspired algorithms.