beesalgorithm is a population-based method that is a computational bound algorithm whose inspired by the natural behavior of honey bees to finds a near-optimal solution for the search problem. Recently, many parallel...
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beesalgorithm is a population-based method that is a computational bound algorithm whose inspired by the natural behavior of honey bees to finds a near-optimal solution for the search problem. Recently, many parallel swarm based algorithms have been developed for running on GPU (Graphic Processing Unit). Since nowadays developing a parallel Bee algorithm running on the GPU becomes very important. In this paper, we extend the beesalgorithm (CUBA (i.e. CUDA based beesalgorithm)) in order to be run on the CUDA (Compute Unified Device Architecture). CUBA (CUDA based beesalgorithm). We evaluate the performance of CUBA by conducting some experiments based on numerous famous optimization problems. Results show that CUBA significantly outperforms standard beesalgorithm in numerous different optimization problems. (C) 2013 Elsevier B.V. All rights reserved.
beesalgorithm is one of the optimization algorithms inspired from the natural foraging ways of the honey bees of finding the best solution. It is an iteration algorithm; therefore, it is suffering from slow convergen...
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beesalgorithm is one of the optimization algorithms inspired from the natural foraging ways of the honey bees of finding the best solution. It is an iteration algorithm; therefore, it is suffering from slow convergence. The other downside of the Bee algorithm is that it has needless computation. This means that it spends a long time for the beesalgorithm converge the optimum solution. In this study, the parallel bees algorithm technique is proposed for overcoming of this issue. Due to that, this would lead to reduce the required time to get a solution with faster results accuracy than original beesalgorithm.
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