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Inspired by the behavior of cockroaches in nature, this paper presents a new optimization algorithm called Cockroach colony optimization(CCO). In the CCO algorithm, nests of cockroaches are placed at the“corner” of the search space. The current best solution to the optimization problem called food can split some of the search targets by applying the logistic multi-peak map and the margin control strategies. By using a particular search scheme, the individual cockroaches can accomplish a highly efficient global and local search in each crawling process from a nest to a search target. The paper provides a formal convergence proof for the CCO algorithm. Experiment results show that the CCO algorithm can be applied to solve global numerical optimization problems with the characteristics of quick convergence and high precision.
Inspired by the behavior of cockroaches in nature, this paper presents a new optimization algorithm called Cockroach colony optimization (CCO). In the CCO algorithm, nests of cockroaches are placed at the “corner ” of the search space. to the optimization problem called food can split some of the search targets by applying the logistic multi-peak map and the margin control strategies. By using a certain search scheme, the individual cockroaches can accomplish a highly efficient global and local search in each crawling process The paper provides a formal convergence proof for the CCO algorithm. Experiment results show that the CCO algorithm can be applied to solve global numerical optimization problems with the characteristics of quick convergence and high precision.