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ABC is an optimization technique, used in finding the best solution from all feasible solutions. However, there is still an insufficiency in ABC regarding improvement in exploitation and convergence speed. In order to improve the performance of ABC we used mean mutation operator (MMO), which uses a linear combination of Gaussian and Cauchy distributions. This convoluted distribution produces larger...
Differential Evolution (DE) algorithm has been shown to be powerful for many real optimization problems. In traditional DE and its variant algorithms, there are three or more candidates used in the step of mutation, which is one of the three typical operation steps: mutation, crossover and selection. To simplify the mutation, we propose a novel evolution algorithm which needs only two individuals...
In recent years, the Particle Swarm Optimization has rapidly gained increasing popularity and many variants and hybrid approaches have been proposed to improve it. Motivated by the behavior and the proximity characteristics of the social and cognitive experience of each particle in the swarm, we develop a hybrid approach that combines the Particle Swarm Optimization and the Differential Evolution...
Although there exist a lot of approaches to solve constrained optimization problem, few of them makes use of the knowledge obtained in the searching process. In the paper, a new algorithm called nearest neighbor evolutionary algorithm (NNE) is proposed to solve the constrained optimization problem. NNE not only performs global search and local search in the searching process, but also considers the...
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