Work

SLSL-QPSO: Quantum-behaved particle swarm optimization with short-lived swarm layers

Year: 2023

Type: software-paper

Abstract: SLSL-QPSO is a software that can find the optimal value of a function. It improves over the Quantum-behaved Particle Swarm Optimization (QPSO) algorithms by leveraging the concept of living and death as swarm layers like the parameter optimization in the Optimized PSO (OPSO) but without the super swarm, the Lévy mutation, the scoped contradiction-expansion coefficient, and the selection of effective layers. Experimental results demonstrate that SLSL-QPSO has superior performance in finding better optimal than QPSO and several other variants thus providing a competitive solution to optimization problems.

Source: SoftwareX

DOI: 10.1016/j.softx.2023.101536

Authors: Kang Liang, Zhang Xiukai, Oleg Krakhmalev

Institutions: Shanghai Polytechnic University, Financial University

Language: English

Topic: Metaheuristic Optimization Algorithms Research

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $760

Funder: Ministry of Education of the People's Republic of China

OpenAlex ID: W4387936732

Cites: 26

Cited by: 6

Related to: 10