A Fast Particle Swarm Optimization Algorithm with Cauchy Mutation and Natural Selection Strategy

Li, Changhe; Liu, Yong; Zhou, Aimin; Kang, Lishan; Wang, Hui

doi:10.1007/978-3-540-74581-5_37

Cited by 46 publications

(22 citation statements)

References 8 publications

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“…To validate the proposed technique unimodal and multimodal benchmark functions were used. Li et al (2007) introduced mutation operator and crossover technique on global best particles to leads the swarm toward optimal solution. This technique implemented on 8 functions with less than 30 dimensions.…”

Section: Literature Reviewmentioning

confidence: 99%

A hybrid particle swarm optimization (PSO) with chi-square and stable mutation jump strategy

Anum

Imran

Hahsim

et al. 2016

Int. j. adv. appl. sci

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Particle Swarm is a heuristic technique based on collective behavior of birds. Several researches depicts that the PSO suffers from untimely convergence. To defeat the issue of untimely convergence in PSO several solutions are proposed to increase the performance in term of accuracy. This paper suggests a new hybrid mutation operator which used Chi-square and stable distribution. The hybrid mutation operator leads the swarm from local minima to global minima for better solution. To validate the new hybrid scheme, a 12 benchmark optimization functions are used in experiment and compared the result with pervious 6 variants of PSO, proposed variant achieved better results than previous 6 variants.

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Section: Literature Reviewmentioning

confidence: 99%

A hybrid particle swarm optimization (PSO) with chi-square and stable mutation jump strategy

Anum

Imran

Hahsim

et al. 2016

Int. j. adv. appl. sci

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show abstract

“…FPSO [12] combines PSO with Cauchy mutation and evolutionary selection strategy. Experimental results show that it keeps the fast convergence speed characteristic of PSO, and greatly overcomes the tendency of trapping into local optimum of PSO.…”

Section: Particle Swarm Optimizationmentioning

confidence: 99%

“…One parent swarm maintains the diversity and detects the promising search area in the whole search space using the fast evolutionary programming (FEP) algorithm [17], and a group of child swarms explore the local area to search for the local optima using a fast PSO (FPSO) [12] algorithm. This mechanism makes the child swarms spread out over the highest multiple peaks, as many as possible, and FPSO [12] guarantees to converge onto a local optimum in a short time.…”

Section: Introductionmentioning

confidence: 99%

Fast Multi-Swarm Optimization for Dynamic Optimization Problems

Yang

2008

2008 Fourth International Conference on Natural Computation

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“…A hybrid technique that combines GA and PSO, called genetic swarm optimization (GSO), was proposed by Grimaldi et al [5] for solving an electromagnetic optimization problem. Li and Wang et al [6,7] proposed a hybrid PSO using Cauchy mutation to reduce the probability of trapping local optima for PSO.…”

Section: Introductionmentioning

confidence: 99%

An Island Based Hybrid Evolutionary Algorithm for Optimization

Yang

2008

Lecture Notes in Computer Science

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Abstract. Evolutionary computation has become an important problem solving methodology among the set of search and optimization techniques. Recently, more and more different evolutionary techniques have been developed, especially hybrid evolutionary algorithms. This paper proposes an island based hybrid evolutionary algorithm (IHEA) for optimization, which is based on Particle swarm optimization (PSO), Fast Evolutionary Programming (FEP), and Estimation of Distribution Algorithm (EDA). Within IHEA, an island model is designed to cooperatively search for the global optima in search space. By combining the strengths of the three component algorithms, IHEA greatly improves the optimization performance of the three basic algorithms. Experimental results demonstrate that IHEA outperforms all the three component algorithms on the test problems.

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A Fast Particle Swarm Optimization Algorithm with Cauchy Mutation and Natural Selection Strategy

Cited by 46 publications

References 8 publications

A hybrid particle swarm optimization (PSO) with chi-square and stable mutation jump strategy

A hybrid particle swarm optimization (PSO) with chi-square and stable mutation jump strategy

Fast Multi-Swarm Optimization for Dynamic Optimization Problems

An Island Based Hybrid Evolutionary Algorithm for Optimization

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