ScholarLens Back to search
2007•Computer Knowledge and TechnologyRequires access

Summary of Knapsack Problems Based on Particle Swarm Optimization

Lei Wang

Open publisher page 0 citations

Abstract

Particle Swarm Optimization is an optimization algorithm based on swarm intelligence,the advantage of PSO is little individual amount,simply counting and good robustness, but PSO easily slump into best local extremum,and rapidity of convergence is slowly in the last stage of evolution. This paper introduced the fundamental principle, parameter settings and optimization of PSO. Model of 0-1 Knapsack Problem and solution are involved in this paper.

About this research paper

What this paper is about

Particle Swarm Optimization is an optimization algorithm based on swarm intelligence,the advantage of PSO is little individual amount,simply counting and good robustness, but PSO easily slump into best local extremum,and rapidity of convergence is slowly in the last stage of evolution. This paper introduced the fundamental principle, parameter settings and optimization of PSO. Model of 0-1 Knapsack Problem and solution are involved in this paper.

Why it matters

A significance statement is not available in the OpenAlex record.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Particle Swarm Optimization is an optimization algorithm based on swarm intelligence,the advantage of PSO is little individual amount,simply counting and good robustness, but PSO easily slump into best local extremum,and rapidity of convergence is slowly in the last stage of evolution. This paper introduced the fundamental principle, parameter settings and optimization of PSO. Model of 0-1 Knapsack Problem and solution are involved in this paper.

Key concepts: Knapsack problem, Particle swarm optimization, Mathematical optimization, Multi-swarm optimization, Computer science, Robustness (evolution), Metaheuristic, Convergence (economics)

Related papers

Related paper 1Related paper 2Related paper 3
Back to paper searchBrowse research topicsOriginal source
Summary of Knapsack Problems Based on Particle Swarm Optimization — Research Paper | ScholarLens