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  1. Swarm Intelligence
  2. Swarm Intelligence : Volume 6
  3. Swarm Intelligence : Volume 6, Issue 4, December 2012
  4. The dynamics of ant colony optimization algorithms applied to binary chains
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Swarm Intelligence : Volume 11
Swarm Intelligence : Volume 10
Swarm Intelligence : Volume 9
Swarm Intelligence : Volume 8
Swarm Intelligence : Volume 7
Swarm Intelligence : Volume 6
Swarm Intelligence : Volume 6, Issue 4, December 2012
ARGoS: a modular, parallel, multi-engine simulator for multi-robot systems
Set-based particle swarm optimization applied to the multidimensional knapsack problem
The dynamics of ant colony optimization algorithms applied to binary chains
Swarm Intelligence : Volume 6, Issue 3, September 2012
Swarm Intelligence : Volume 6, Issue 2, June 2012
Swarm Intelligence : Volume 6, Issue 1, March 2012
Swarm Intelligence : Volume 5
Swarm Intelligence : Volume 4
Swarm Intelligence : Volume 3
Swarm Intelligence : Volume 2
Swarm Intelligence : Volume 1

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The dynamics of ant colony optimization algorithms applied to binary chains

Content Provider SpringerLink
Author Iacopi, Claudio Palmer, Phil
Copyright Year 2012
Abstract In the last decade Ant Colony Optimization (ACO) algorithms have received increasing attention due to their flexibility and adaptability to different applications. Despite these advantages, their design and analysis are still critical issues; research on formal methods could increase the reliability of these systems and extend their applications to critical scenarios such as space or military.This paper aims at exploring the potential of formal modelling techniques already developed for studying dynamical systems. The benefits of these techniques are shown in the analysis of a generic ACO algorithm applied to problems modelled as binary chains. The theoretical model developed is able to give new insights on the overall system dynamics, predicting the system long-term behaviours and the influence of specific parameters on such behaviours. This paper first offers a complete stability analysis for a basic problem providing an easy description of the key concepts before generalizing the model to problems of n nodes, allowing its application to real problems. The picture of the system dynamics is then completed by a convergence time analysis, which is necessary to draw sensible conclusions.
Starting Page 343
Ending Page 377
Page Count 35
File Format PDF
ISSN 19353812
Journal Swarm Intelligence
Volume Number 6
Issue Number 4
e-ISSN 19353820
Language English
Publisher Springer US
Publisher Date 2012-12-06
Publisher Place Boston
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Ant colony optimization algorithm Change of stability Dynamical systems ODE Equilibrium point Parameter impact analysis Artificial Intelligence (incl. Robotics) Computer Systems Organization and Communication Networks ApplicationMathematics/Computational Methods of Engineering Communications Engineering, Networks Computer Communication Networks
Content Type Text
Resource Type Article
Subject Artificial Intelligence
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