Golden ball: a novel meta-heuristic to solve combinatorial optimization problems based on soccer concepts

E. Osaba; F. Diaz; E. Onieva

doi:10.1007/s10489-013-0512-y

Golden ball: a novel meta-heuristic to solve combinatorial optimization problems based on soccer concepts

E. Osaba
, F. Diaz
, E. Onieva^*

^*Autor correspondiente de este trabajo

University of Deusto

Producción científica: Contribución a una revista › Artículo › revisión exhaustiva

90 Citas (Scopus)

Resumen

In this paper, a new multiple population based meta-heuristic to solve combinatorial optimization problems is introduced. This meta-heuristic is called Golden Ball (GB), and it is based on soccer concepts. To prove the quality of our technique, we compare its results with the results obtained by two different Genetic Algorithms (GA), and two Distributed Genetic Algorithms (DGA) applied to two well-known routing problems, the Traveling Salesman Problem (TSP) and the Capacitated Vehicle Routing Problem (CVRP). These outcomes demonstrate that our new meta-heuristic performs better than the other techniques in comparison. We explain the reasons of this improvement.

Idioma original	Inglés
Páginas (desde-hasta)	145-166
Número de páginas	22
Publicación	Applied Intelligence
Volumen	41
N.º	1
DOI	https://doi.org/10.1007/s10489-013-0512-y
Estado	Publicada - 1 jul 2014
Publicado de forma externa	Sí

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abstract = "In this paper, a new multiple population based meta-heuristic to solve combinatorial optimization problems is introduced. This meta-heuristic is called Golden Ball (GB), and it is based on soccer concepts. To prove the quality of our technique, we compare its results with the results obtained by two different Genetic Algorithms (GA), and two Distributed Genetic Algorithms (DGA) applied to two well-known routing problems, the Traveling Salesman Problem (TSP) and the Capacitated Vehicle Routing Problem (CVRP). These outcomes demonstrate that our new meta-heuristic performs better than the other techniques in comparison. We explain the reasons of this improvement.",

keywords = "Combinatorial optimization, Distributed genetic algorithm, Golden ball, Intelligent transportation systems, Meta-heuristics, Routing problems",

author = "E. Osaba and F. Diaz and E. Onieva",

note = "Publisher Copyright: {\textcopyright} 2014, Springer Science+Business Media New York.",

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doi = "10.1007/s10489-013-0512-y",

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AU - Diaz, F.

AU - Onieva, E.

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N2 - In this paper, a new multiple population based meta-heuristic to solve combinatorial optimization problems is introduced. This meta-heuristic is called Golden Ball (GB), and it is based on soccer concepts. To prove the quality of our technique, we compare its results with the results obtained by two different Genetic Algorithms (GA), and two Distributed Genetic Algorithms (DGA) applied to two well-known routing problems, the Traveling Salesman Problem (TSP) and the Capacitated Vehicle Routing Problem (CVRP). These outcomes demonstrate that our new meta-heuristic performs better than the other techniques in comparison. We explain the reasons of this improvement.

AB - In this paper, a new multiple population based meta-heuristic to solve combinatorial optimization problems is introduced. This meta-heuristic is called Golden Ball (GB), and it is based on soccer concepts. To prove the quality of our technique, we compare its results with the results obtained by two different Genetic Algorithms (GA), and two Distributed Genetic Algorithms (DGA) applied to two well-known routing problems, the Traveling Salesman Problem (TSP) and the Capacitated Vehicle Routing Problem (CVRP). These outcomes demonstrate that our new meta-heuristic performs better than the other techniques in comparison. We explain the reasons of this improvement.

KW - Combinatorial optimization

KW - Distributed genetic algorithm

KW - Golden ball

KW - Intelligent transportation systems

KW - Meta-heuristics

KW - Routing problems

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Golden ball: a novel meta-heuristic to solve combinatorial optimization problems based on soccer concepts

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