Work

A Novel Adaptive Particle Swarm Optimization

Year: 2013

Type: article

Abstract: Particle swarm optimization (PSO) is a stochastic search technique for solving optimization problems, which has been proven to be efficient and effective in wide applications.However, the PSO can easily fly into the local optima and lack the ability to jump out of the local optima.A novel adaptive PSO is proposed by evaluating convergence of the fitness value.The novel mechanism is to ensure the diversity of particles.Simulations for benchmark test functions have illustrated that the proposed algorithm possesses better ability to find the global optima than other variants and is an effective global optimization tool.

Source: Journal of Engineering Science and Technology Review

DOI: 10.25103/jestr.062.37

Authors: Xiaobing Yu, Jun Guo

Institutions: Nanjing University of Information Science and Technology, Wuhan University of Technology

Language: English

Topic: Metaheuristic Optimization Algorithms Research

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

Funders: Government of Jiangsu Province, Priority Academic Program Development of Jiangsu Higher Education Institutions

OpenAlex ID: W2184433878

FWCI: 0.261

Cites: 14

Cited by: 5

Related to: 10