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This paper presents a novel optimization algorithm based on competitive behavior of various creatures such as birds, cats, bees and ants to survive in nature. In the proposed method, a competition is designed among all aforementioned creatures according to their performances. Every optimization algorithm can be appropriate for some objective functions and may not be appropriate for another. Due to...
Optimization methods based on swarm intelligence, have been used widely in science. These methods are mainly inspired from swarm behavior of animals in nature. Grey Wolf Optimizer (GWO) is a meta-heuristic approach simulating wolves' behavior while they are hunting. In this research, it has been tried to improve the final results of the original version of algorithm, compared with other common optimization...
In this paper, we present a new algorithm binary discrete optimization method based on cat swarm optimization (CSO). BCSO is a binary version of CSO generated by observing the behaviors of cats. As in CSO, BCSO consists of two modes of operation: tracing mode and seeking mode. The BCSO presented in this paper is implemented on a number of benchmark optimization problems and zero-one knapsack problem...
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