@inproceedings{70ba304bb6434b9bb830ca6247eb2c95,
title = "Comparison between golden ball meta-heuristic, evolutionary simulated annealing and tabu search for the traveling salesman problem",
abstract = "The Golden Ball is a multi-population meta-heuristic based on soccer concepts. It was first designed to solve combinatorial optimization problems. Until now, it has been tested with different kind of problems, but its efficiency has only been compared with some classical algorithms, such as different kind of Genetic Algorithms and Distributed Genetic Algorithms. In this work, the performance of the Golden Ball is compared with the ones obtained by two famous and widely used techniques: an Evolutionary Simulated Annealing and a Tabu Search. These both meta-heuristics are two of the most used ones along the history for solving optimization problems. In this first study, the comparison is performed for the well-known Traveling Salesman Problem.",
keywords = "Golden ball, Simulated annealing, TSP, Tabu search, Traveling salesman problem",
author = "Eneko Osaba and Roberto Carballedo and Pedro Lopez-Garcia and Fernando Diaz",
note = "Publisher Copyright: {\textcopyright} 2016 Copyright held by the owner/author(s).; 2016 Genetic and Evolutionary Computation Conference, GECCO 2016 Companion ; Conference date: 20-07-2016 Through 24-07-2016",
year = "2016",
month = jul,
day = "20",
doi = "10.1145/2908961.2931634",
language = "English",
series = "GECCO 2016 Companion - Proceedings of the 2016 Genetic and Evolutionary Computation Conference",
publisher = "Association for Computing Machinery, Inc",
pages = "1469--1470",
editor = "Tobias Friedrich",
booktitle = "GECCO 2016 Companion - Proceedings of the 2016 Genetic and Evolutionary Computation Conference",
}