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Cloud estimation of distribution particle swarm optimizer combining PSO and cloud model is introduced. In the algorithm's offspring generation scheme, new particles are generated in the cloud estimation of distribution way or in the PSO way. The innovation of the algorithm is production of cloud particles according to the cloud model theory. The cognitive population obtained during optimization is...
This paper proposes a method of target location based on the adaptive particle swarm optimization algorithm in view of the shortcoming that the current localization solution is complex, and the standard particle swarm optimizer algorithm has low convergence rate and is easy to be trapped in local optimum. In the algorithm, the adaptive inertia weight can balance global and local search ability, and...
In order to improve the global search ability and the convergence speed of the Artificial Fish Swarm Algorithm (AFSA), a novel Quantum Artificial Fish Swarm Algorithm (QAFSA) which is based on the concepts and principles of quantum computing, such as the quantum bit and quantum gate is proposed in this paper. The position of the Artificial Fish (AF) is encoded by the angle in [0, 2π] based on the...
Linear antenna array design is one of the most important electromagnetic optimization problems of current interest. This article describes the application of a recently developed metaheuristic algorithm, known as the invasive weed optimization (IWO), to optimize the spacing between the elements of the linear array to produce a radiation pattern with minimum side lobe level and null placement control...
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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