Automatically Generated Algorithms for the Vertex Coloring Problem
Guardado en:
| Publicado en: | PLoS One vol. 8, no. 3 (Mar 2013), p. e58551 |
|---|---|
| Autor principal: | |
| Otros Autores: | , |
| Publicado: |
Public Library of Science
|
| Materias: | |
| Acceso en línea: | Citation/Abstract Full Text Full Text - PDF |
| Etiquetas: |
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
MARC
| LEADER | 00000nab a2200000uu 4500 | ||
|---|---|---|---|
| 001 | 1330898270 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 1932-6203 | ||
| 024 | 7 | |a 10.1371/journal.pone.0058551 |2 doi | |
| 035 | |a 1330898270 | ||
| 045 | 2 | |b d20130301 |b d20130331 | |
| 084 | |a 174835 |2 nlm | ||
| 100 | 1 | |a Carlos Contreras Bolton | |
| 245 | 1 | |a Automatically Generated Algorithms for the Vertex Coloring Problem | |
| 260 | |b Public Library of Science |c Mar 2013 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a The vertex coloring problem is a classical problem in combinatorial optimization that consists of assigning a color to each vertex of a graph such that no adjacent vertices share the same color, minimizing the number of colors used. Despite the various practical applications that exist for this problem, its NP-hardness still represents a computational challenge. Some of the best computational results obtained for this problem are consequences of hybridizing the various known heuristics. Automatically revising the space constituted by combining these techniques to find the most adequate combination has received less attention. In this paper, we propose exploring the heuristics space for the vertex coloring problem using evolutionary algorithms. We automatically generate three new algorithms by combining elementary heuristics. To evaluate the new algorithms, a computational experiment was performed that allowed comparing them numerically with existing heuristics. The obtained algorithms present an average 29.97% relative error, while four other heuristics selected from the literature present a 59.73% error, considering 29 of the more difficult instances in the DIMACS benchmark. | |
| 610 | 4 | |a Kluwer Academic Publishers | |
| 651 | 4 | |a New York | |
| 651 | 4 | |a Chile | |
| 651 | 4 | |a United States--US | |
| 653 | |a Hybridization | ||
| 653 | |a Integer programming | ||
| 653 | |a Computation | ||
| 653 | |a Computer science | ||
| 653 | |a Algorithms | ||
| 653 | |a Combinatorial analysis | ||
| 653 | |a Coloring | ||
| 653 | |a Computer applications | ||
| 653 | |a Color | ||
| 653 | |a Heuristic | ||
| 653 | |a Evolutionary algorithms | ||
| 653 | |a Competition | ||
| 653 | |a Graph theory | ||
| 653 | |a Graph coloring | ||
| 653 | |a Genetic algorithms | ||
| 653 | |a Problem solving | ||
| 653 | |a Economic | ||
| 653 | |a Methods | ||
| 653 | |a Automation | ||
| 653 | |a Artificial intelligence | ||
| 700 | 1 | |a Gatica, Gustavo | |
| 700 | 1 | |a Parada, Víctor | |
| 773 | 0 | |t PLoS One |g vol. 8, no. 3 (Mar 2013), p. e58551 | |
| 786 | 0 | |d ProQuest |t Health & Medical Collection | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/1330898270/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/1330898270/fulltext/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/1330898270/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |