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Quantum-behaved particle swarm optimization (QPSO) algorithm theoretically guarantees global convergence and has been implemented on a wide suite of continuous optimization problems. In this paper, the nonlinear multimodal optimization problem of high pass FIR filter design is investigated using the weighted mean best QPSO algorithm (WQPSO). The results are compared with competitive techniques such...
Particle Swarm Optimization (PSO) is arguably one of the most popular nature- inspired algorithms for real parameter optimization at present. The existing theoretical research on PSO is mostly based on the gbest (global best) particle topology, which usually is susceptible to false or premature convergence over multi-modal fitness landscapes. The present standard PSO (SPSO 2007) uses an lbest (local...
This paper introduces an improved artificial colony algorithm. In the algorithm, a new search iteration operator based on the fixed point theorem of Contractive Mapping in Banach Spaces is proposed. In this work, the improved artificial colony algorithm is used to 10 multivariable benchmark functions. The simulation results show that the algorithm possesses an excellent performance in the global optimization,...
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