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Second order swarm intelligence

Ramos, Vitorino; Rodrigues, David and Louçã, Jorge (2013). Second order swarm intelligence. Lecture Notes in Computer Science, 8073 pp. 411–420.

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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
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.
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
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
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