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

被引：53

作者：

Osaba, E. ^{[1
]}

Diaz, F. ^{[1
]}

Onieva, E. ^{[1
]}

机构：

[1] Univ Deusto, Deusto Inst Technol DeustoTech, Bilbao 48007, Spain

来源：

APPLIED INTELLIGENCE | 2014年 / 41卷 / 01期

关键词：

Meta-heuristics; Golden ball; Distributed genetic algorithm; Routing problems; Combinatorial optimization; Intelligent transportation systems; VEHICLE-ROUTING PROBLEM; TRAVELING SALESMAN PROBLEM; EVOLUTIONARY ALGORITHM; GENETIC ALGORITHM;

D O I：

10.1007/s10489-013-0512-y

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：145 / 166

页数：22

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