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This is a new optimization algorithm which mimic the behavior of mosquito to find a hole in mosquito net, if any. Both the flying and sliding motion of the mosquito have been modelled and incorporated in the algorithm. The algorithm was tested for global minima on different type of benchmark functions of various dimension and modality. Namely Gramacy & Lee, Ackley, Rastrigin, Rosenbrock, Griewank...
Particle swarm optimization groups adjust the search strategy to obtain evolution by fully sharing information. Rational utilize of the group information also determine the efficiency and performance of particle swarm algorithm. The group historical experience particle swarm optimization (GHEPSO) is proposed, particles are not influenced only by the group optimal position of the current generation...
Many practical applications are dynamic over time, which require optimization algorithms not only to converge to optimum as soon as possible but also to track the changing optimum. In this paper, a Cooperative Dual-swarm PSO (CDPSO) is proposed to deal with dynamic optimization problems. CDPSO adopts dual-swarm structure to keep swarm diversity and track the changing optimum. Fractional Global Best...
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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