title: An improved cockroach swarm optimization.
abstract: Hunger component is introduced to the existing cockroach swarm optimization (CSO) algorithm to improve its searching ability and population diversity. The original CSO was modelled with three components: chase-swarming, dispersion, and ruthless; additional hunger component which is modelled using partial differential equation (PDE) method is included in this paper. An improved cockroach swarm optimization (ICSO) is proposed in this paper. The performance of the proposed algorithm is tested on well known benchmarks and compared with the existing CSO, modified cockroach swarm optimization (MCSO), roach infestation optimization RIO, and hungry roach infestation optimization (HRIO). The comparison results show clearly that the proposed algorithm outperforms the existing algorithms.
authors: School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Westville, Durban 4000, South Africa.
authors: I C
authors: IC
authors: Obagbuwa
authors: School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Westville, Durban 4000, South Africa.
authors: A O
authors: AO
authors: Adewumi
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D008962:Models, Theoretical