Ramos, Vitorino; Rodrigues, David and Louçã, Jorge
(2013).
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(Accepted Manuscript)
Due to publisher licensing restrictions, this file is not available for public download |
| DOI (Digital Object Identifier) Link: | https://doi.org/10.1007/978-3-642-40846-5_41 |
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| Google Scholar: | Look up in Google Scholar |
Abstract
An artificial Ant Colony System (ACS) algorithm to solve general-purpose combinatorial Optimization Problems (COP) that extends previous AC models [21] by the inclusion of a negative pheromone, is here described. Several Travelling Salesman Problem (TSP) were used as benchmark. We show that by using two different sets of pheromones, a second-order co-evolved compromise between positive and negative feedbacks achieves better results than single positive feedback systems. The algorithm was tested against known NP-complete combinatorial Optimization Problems, running on symmetrical TSP's. We show that the new algorithm compares favourably against these benchmarks, accordingly to recent biological findings by Robinson [26,27], and Gruter [28] where "No entry" signals and negative feedback allows a colony to quickly reallocate the majority of its foragers to superior food patches. This is the first time an extended ACS algorithm is implemented with these successful characteristics.
| Item Type: | Journal Item |
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| Copyright Holders: | 2013 Springer-Verlag Berlin Heidelberg |
| ISSN: | 0302-9743 |
| Extra Information: | Hybrid Artificial Intelligent Systems
8th International Conference, HAIS 2013, Salamanca, Spain, September 11-13, 2013. Proceedings Editors: Jeng-Shyang Pan, Marios M. Polycarpou, Michał Woźniak, André C. P. L. F. de Carvalho, Héctor Quintián, Emilio Corchado ISBN: 978-3-642-40845-8 pp,411-420 |
| Keywords: | self-organization; stigmergy; co-evolution; swarm intelligence; dynamic optimization; foraging; cooperative learning; combinatorial optimization problems; symmetrical traveling salesman problems (TSP) |
| Academic Unit/School: | Faculty of Science, Technology, Engineering and Mathematics (STEM) > Engineering and Innovation Faculty of Science, Technology, Engineering and Mathematics (STEM) |
| Item ID: | 38706 |
| Depositing User: | David Rodrigues |
| Date Deposited: | 10 Oct 2013 10:47 |
| Last Modified: | 11 Sep 2018 00:38 |
| URI: | http://oro.open.ac.uk/id/eprint/38706 |
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