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Article Bee Colony (ABC) is one of the most recently introduced algorithms based on the intelligent foraging behavior of a honey bee swarm. This paper presents a variation on the original ABC algorithm, namely the Cooperative Article Bee Colony (CABC), which significantly improves the original ABC in solving complex optimization problems. In this work, CABC algorithm is used for optimizing six widely-used...
Opposition-based Learning (OBL) is a new concept in machine intelligence, and has been proven to be an effective method to Differential Evolution (DE), Particle Swarm Optimization (PSO) and other population-based algorithms in solving many optimization problems. Opposition-based DE (ODE) is one of successful applications of OBL, which shows faster and more robust convergence than classical DE. In...
A self-adaptive mutation-particle swarm optimization algorithm is proposed in this paper. In this algorithm, firstly, to avoid the randomness of updating particle velocity, a modified velocity updating formula of the particle which varies with convergence factor and the diffusion factor is proposed by adaptive inertia weight. Secondly, the introduction of stochastic mutation operators enhances the...
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