Journal ArticleDOI
Convergence analysis and improvements of quantum-behaved particle swarm optimization
TLDR
It is proved that the QPSO algorithm is a form of contraction mapping and can converge to the global optimum and a new definition for the convergence rate of a stochastic algorithm as well as definitions for three types of convergence according to the correlations between the convergence rates and the objective function values are provided.About:
This article is published in Information Sciences.The article was published on 2012-06-01. It has received 173 citations till now. The article focuses on the topics: Particle swarm optimization & Rate of convergence.read more
Citations
More filters
Journal ArticleDOI
A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications
TL;DR: This survey presented a comprehensive investigation of PSO, including its modifications, extensions, and applications to the following eight fields: electrical and electronic engineering, automation control systems, communication theory, operations research, mechanical engineering, fuel and energy, medicine, chemistry, and biology.
Journal ArticleDOI
Quantum-behaved particle swarm optimization: Analysis of individual particle behavior and parameter selection
TL;DR: This paper presents a comprehensive analysis of the QPSO algorithm, and performs empirical studies on a suite of well-known benchmark functions to show how to control and select the value of the CE coefficient in order to obtain generally good algorithmic performance in real world applications.
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
Solving the Power Economic Dispatch Problem With Generator Constraints by Random Drift Particle Swarm Optimization
TL;DR: The experimental results show that the RDPSO method performs better in solving the ED problems than any other tested optimization techniques.
Journal ArticleDOI
Multidimensional color image storage, retrieval, and compression based on quantum amplitudes and phases
TL;DR: A new representation method for multidimensional color images, called an n -qubit normal arbitrary superposition state (NASS), where n qubits represent the colors and coordinates of 2 n pixels, is proposed.
References
More filters
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 modified particle swarm optimizer
Yuhui Shi,Russell C. Eberhart +1 more
TL;DR: A new parameter, called inertia weight, is introduced into the original particle swarm optimizer, which resembles a school of flying birds since it adjusts its flying according to its own flying experience and its companions' flying experience.
Journal ArticleDOI
The particle swarm - explosion, stability, and convergence in a multidimensional complex space
M. Clerc,James Kennedy +1 more
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
Empirical study of particle swarm optimization
Yuhui Shi,Russell C. Eberhart +1 more
TL;DR: The experimental results show that the PSO is a promising optimization method and a new approach is suggested to improve PSO's performance near the optima, such as using an adaptive inertia weight.