Binary Cuckoo Optimization Algorithm

In this paper Binary Cuckoo Optimization Algorithm (BCOA) is introduced. Recently introduced COA has proven its excellent capabilities, such as faster convergence and better global minimum achievement. As the introduced COA is originally designed to solve continuous optimization problems, in this paper some of COA components are modified in a way that it can be applied on problems with discrete and binary nature. First, we present results on instance of knapsack problem to illustrate the adequacy of the proposed approach for combinatorial optimization. Then, to prove the BCOA performance and illustrate capability of the proposed binary version, it is applied to solve wide range of optimization problems. The comparative results between BCOA, Binary Genetic Algorithm (BGA), Binary Particle Swarm Optimization (BPSO) and Binary Gravitational Search Algorithm (BGSA) show that Binary Cuckoo Optimization Algorithm (BCOA) has much faster convergence, similar to its continuous version.