Abstract Particle Swarm Optimization has been extensively researched and applied to tackle
optimization problems due to the ease in implementation and less number of parameters to …

An improved quantum‐behaved particle swarm optimization with elitist breeding (EB‐QPSO)
for unconstrained optimization is presented and empirically studied in this paper. In EB …

Quantum-behaved particle swarm optimization (QPSO) algorithm is a global convergence
guaranteed algorithms, which outperforms original PSO in search ability but has fewer …

In this paper, in order to search the global optimum solution with a very fast convergence
speed across the whole search space, we propose a partitioned and cooperative quantum …

Based on the previous introduced Quantum-behaved Particle Swarm Optimization (QPSO),
in this paper, a revised QPSO with novel iterative equation is proposed. While the iterative …

Abstract Particle Swarm Optimization (PSO) is a population-based metaheuristic belonging
to the class of Swarm Intelligence (SI) algorithms. Nowadays, its effectiveness on many hard …

This paper proposes a dynamic-context cooperative quantum-behaved particle swarm
optimization algorithm. The proposed algorithm incorporates a new method for dynamically …

Based on the problem of traditional particle swarm optimization (PSO) easily trapping into
local optima, quantum theory is introduced into PSO to strengthen particles' diversities and …

Quantum-behaved particle swarm optimization (QPSO), a novel variant of PSO inspired by
quantum mechanics, is a global convergence guaranteed algorithm, which outperforms the …

Motivated by the particle swarm optimization (PSO) and quantum computing theory, we have
presented a quantum variant of PSO (QPSO) mutated with Cauchy operator and natural …