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Proceedings ArticleDOI

A quantum particle swarm optimization

Shuyuan Yang, +2 more
- Vol. 1, pp 320-324
TLDR
A new discrete particle swarm optimization algorithm based on quantum individual is proposed, which is simpler and more powerful than the algorithms available.
Abstract
The particle swarm optimization algorithm is a new methodology in evolutionary computation. It has been found to be extremely effective is solving a wide range of engineering problems, however, it is of low efficiency in dealing with the discrete problems. In this paper, a new discrete particle swarm optimization algorithm based on quantum individual is proposed. It is simpler and more powerful than the algorithms available. The simulation experiments and its application in the CDMA also prove its high efficiency.

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Citations
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Journal ArticleDOI

Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems

TL;DR: This paper presents a detailed overview of the basic concepts of PSO and its variants, and provides a comprehensive survey on the power system applications that have benefited from the powerful nature ofPSO as an optimization technique.
Journal ArticleDOI

Fifty Years of MIMO Detection: The Road to Large-Scale MIMOs

TL;DR: In this article, the authors provide a recital on the historic heritages and novel challenges facing massive/large-scale multiple-input multiple-output (LS-MIMO) systems from a detection perspective.
Journal ArticleDOI

A review of particle swarm optimization. Part II: hybridisation, combinatorial, multicriteria and constrained optimization, and indicative applications

TL;DR: This paper aims to offer a compendious and timely review of the field and the challenges and opportunities offered by this welcome addition to the optimization toolbox.
Journal ArticleDOI

General Type-2 Fuzzy Logic Systems Made Simple: A Tutorial

TL;DR: This tutorial paper explains four different mathematical representations for general type-2 fuzzy sets (GT2 FS) and demonstrates that for the optimal design of a GT2 FLS, one should use the vertical-slice representation of its GT2 FSs because it is the only one of the four mathematical representations that is parsimonious.
Journal ArticleDOI

Hybrid discrete particle swarm optimization algorithm for capacitated vehicle routing problem

TL;DR: The computational study showed that the proposed algorithm is a feasible and effective approach for capacitated vehicle routing problem, especially for large scale problems.
References
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Proceedings ArticleDOI

Particle swarm optimization

TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
Proceedings ArticleDOI

A new optimizer using particle swarm theory

TL;DR: The optimization of nonlinear functions using particle swarm methodology is described and implementations of two paradigms are discussed and compared, including a recently developed locally oriented paradigm.
Journal ArticleDOI

The particle swarm - explosion, stability, and convergence in a multidimensional complex space

TL;DR: This paper analyzes a particle's trajectory as it moves in discrete time, then progresses to the view of it in continuous time, leading to a generalized model of the algorithm, containing a set of coefficients to control the system's convergence tendencies.
Proceedings ArticleDOI

A discrete binary version of the particle swarm algorithm

TL;DR: The paper reports a reworking of the particle swarm algorithm to operate on discrete binary variables, where trajectories are changes in the probability that a coordinate will take on a zero or one value.
Book ChapterDOI

Parameter Selection in Particle Swarm Optimization

TL;DR: This paper first analyzes the impact that inertia weight and maximum velocity have on the performance of the particle swarm optimizer, and then provides guidelines for selecting these two parameters.