Elite opposition-based social spider optimization algorithm for global function optimization (Q1662596)
From MaRDI portal
 | This is the item page for this Wikibase entity, intended for internal use and editing purposes. Please use this page instead for the normal view: Elite opposition-based social spider optimization algorithm for global function optimization |
scientific article; zbMATH DE number 6920554
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Elite opposition-based social spider optimization algorithm for global function optimization |
scientific article; zbMATH DE number 6920554 |
Statements
Elite opposition-based social spider optimization algorithm for global function optimization (English)
0 references
20 August 2018
0 references
Summary: The Social Spider Optimization algorithm (SSO) is a novel metaheuristic optimization algorithm. To enhance the convergence speed and computational accuracy of the algorithm, in this paper, an elite opposition-based Social Spider Optimization algorithm (EOSSO) is proposed; we use an elite opposition-based learning strategy to enhance the convergence speed and computational accuracy of the SSO algorithm. The 23 benchmark functions are tested, and the results show that the proposed elite opposition-based Social Spider Optimization algorithm is able to obtain an accurate solution, and it also has a fast convergence speed and a high degree of stability.
0 references
social spider optimization
0 references
elite opposition-based learning
0 references
elite opposition-based social spider optimization
0 references
function optimization
0 references
