Name
Title | ||
|---|---|---|
GAAP. genetic algorithm with auxiliary populations applied to continuous optimization problems |
Abstract | ||
|---|---|---|
Genetic algorithms have been used successfully to solve continuous optimization problems. However, an early convergence to low-quality solutions is one of the most common difficulties encountered when using these strategies. In this paper, a method that combines multiple auxiliary populations with the main population of the algorithm is proposed. The role of the auxiliary populations is dual: to prevent or hinder the early convergence to local suboptimal solutions, and to provide a local search mechanism for a greater exploitation of the most promising regions within the search space. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.2498/iti.2012.0382 | Information Technology Interfaces |
Keywords | Field | DocType |
convergence,genetic algorithms,search problems,auxiliary population,continuous optimization problem,convergence,genetic algorithm,local search mechanism,Real coded genetic algorithms,auxiliary populations,continuous optimization,early convergence,exploitation,exploration,local search | Continuous optimization,Population,Mathematical optimization,Premature convergence,Computer science,Meta-optimization,Local search (optimization),Quality control and genetic algorithms,Genetic algorithm,Metaheuristic | Conference |
ISSN | ISBN | Citations |
1334-2762 | 978-1-4673-1629-3 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Leonardo Corbalán | 1 | 4 | 2.90 |
| Waldo Hasperué | 2 | 2 | 2.40 |
| Laura Lanzarini | 3 | 21 | 8.94 |