This paper focuses on discussing how to select parameter when QPSO is practically applied. After the QPSO algorithm is described, the experiment results of ...

This paper presents a comprehensive analysis of the QPSO algorithm. In the theoretical analysis, we analyze the behavior of a single particle in QPSO in terms ...

This paper focuses on discussing how to select parameter when QPSO is practically applied. After the QPSO algorithm is described, the experiment results of ...

SLSL-QPSO is a software that can find the optimal value of a function. It improves over the Quantum-behaved Particle Swarm Optimization (QPSO) algorithms.

Particle Swarm Optimization (PSO) is a population-based evolution- ary search technique, which has comparable performance with Genetic algo- rithm. The existing ...

Sep 1, 2012 · This paper presents a comprehensive analysis of the QPSO algorithm. In the theoretical analysis, we analyze the behavior of a single particle in QPSO in terms ...

This paper focuses on discussing two adaptive parameter control methods for QPSO. After the ideology of QPSO is formulated, the experiment results of stochastic ...

This paper focuses on discussing how to select parameter when QPSO is practically applied, and two parameter control methods are presented and experiment ...

Aug 17, 2022 · This paper introduces a novel variant of the quantum particle swarm optimization algorithm based on the quantum concept of particle-like solitons.

Since the parti- cle's behavior is influenced by the contraction-expansion (CE) coefficient, which is the most important parameter of the algorithm, the goal of ...