Journal ArticleDOI
Enhancing particle swarm optimization using generalized opposition-based learning
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TLDR
An enhanced PSO algorithm called GOPSO is presented, which employs generalized opposition-based learning (GOBL) and Cauchy mutation to overcome the problem of premature convergence when solving complex problems.About:
This article is published in Information Sciences.The article was published on 2011-10-01. It has received 384 citations till now. The article focuses on the topics: Multi-swarm optimization & Particle swarm optimization.read more
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Coordinated scheduling of production and transportation in a two-stage assembly flowshop
TL;DR: In this article, the coordinated scheduling of production and transportation in a two-stage assembly flow shop environment is considered, and a new hybrid meta-heuristic (HGA-OVNS) is proposed to minimize the weighted sum of average arrival time at the customer and total delivery cost.
Journal ArticleDOI
Globally-optimal prediction-based adaptive mutation particle swarm optimization
Quanlong Cui,Qiuying Li,Gaoyang Li,Zhengguang Li,Xiaosong Han,Heow Pueh Lee,Yanchun Liang,Bing-Hong Wang,Jingqing Jiang,Chunguo Wu +9 more
TL;DR: Numerical experiments demonstrate that the proposed GPAM-PSO could improve the accuracy and efficiency remarkably, which means that the combination of the globally-optimal prediction-based search and the adaptive mutation strategy could accelerate the convergence and reduce premature phenomenon effectively.
Journal ArticleDOI
Particle swarm optimization using multi-level adaptation and purposeful detection operators
TL;DR: A sophisticated PSO algorithm based on multi-level adaptation and purposeful detection based on some historical information is proposed to help the population to jump out of local optima and the extensive experimental study on CEC13 test suites illustrates the effectiveness and efficiency of the modified PSO.
Journal ArticleDOI
FIR digital filter design using improved particle swarm optimization based on refraction principle
TL;DR: An improved particle swarm optimization algorithm based on the model of refracting opposite learning, called refrPSO, is applied to design and optimize FIR low pass and high pass digital filters with linear phase.
Journal Article
An Improved Cat Swarm Optimization Algorithm Based on Opposition-Based Learning and Cauchy Operator for Clustering
Yugal Kumar,Gadadhar Sahoo +1 more
TL;DR: The opposition-based learning method is applied to enhance the diversity of the CSO algorithm and the Cauchy mutation operator is used to prevent theCSO algorithm from trapping in local optima.
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.
Journal ArticleDOI
An Introduction to Probability Theory and Its Applications
David A. Freedman,William Feller +1 more
Journal Article
Statistical Comparisons of Classifiers over Multiple Data Sets
TL;DR: A set of simple, yet safe and robust non-parametric tests for statistical comparisons of classifiers is recommended: the Wilcoxon signed ranks test for comparison of two classifiers and the Friedman test with the corresponding post-hoc tests for comparisons of more classifiers over multiple data sets.
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.