Result: Ant Colony Extended: Experiments on the Travelling Salesman Problem

Title:
Ant Colony Extended: Experiments on the Travelling Salesman Problem
Authors:
ESCARIO, Jose B, JIMENEZ, Juan F, GIRON-SIERRA, Jose M
Source:
Expert systems with applications. 42(1):390-410
Publisher Information:
Amsterdam: Elsevier, 2015.
Publication Year:
2015
Physical Description:
print, 3/4 p
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Recherche operationnelle. Gestion, Operational research. Management science, Recherche opérationnelle et modèles formalisés de gestion, Operational research and scientific management, Flots dans les réseaux. Problèmes combinatoires, Flows in networks. Combinatorial problems, Logistique, Logistics, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Informatique théorique, Theoretical computing, Recherche information. Graphe, Information retrieval. Graph, Intelligence artificielle, Artificial intelligence, Autoorganisation, Self organization, Autoorganización, Construction graphe, Graph construction, Construcción grafo, Insecte social, Social insect, Insecto social, Intelligence artificielle, Artificial intelligence, Inteligencia artificial, Intelligence en essaim, Swarm intelligence, Inteligencia de enjambre, Optimisation PSO, Particle swarm optimization, Optimización PSO, Optimisation combinatoire, Combinatorial optimization, Optimización combinatoria, Politique régulation, Regulation policy, Política regulación, Problème combinatoire, Combinatorial problem, Problema combinatorio, Problème commis voyageur, Travelling salesman problem, Problema viajante comercio, Régulation, Regulation(control), Regulación, Système multiagent, Multiagent system, Sistema multiagente, Analyse atteignabilité, Reachability analysis, Análisis de asequibilidad, Optimisation par colonies de fourmis, Ant colony optimization, Algoritmo de las hormigas, Vie artificielle, Artificial life, Vida artificial, Ant Colony Optimisation, Multi-agent system, Self-organisation
Document Type:
Academic journal Article
File Description:
text
Language:
English
Author Affiliations:
Arquitectura de Computadores y Automatica, Universidad Complutense de Madrid, Av. Complutense s/n, 28040 Madrid, Spain
ISSN:
0957-4174
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=28843410
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems

Operational research. Management
Accession Number:
edscal.28843410
Database:
PASCAL Archive

Further Information

Ant Colony Extended (ACE) is a novel algorithm belonging to the general Ant Colony Optimisation (ACO) framework. Two specific features of ACE are: the division of tasks between two kinds of ants, namely patrollers and foragers, and the implementation of a regulation policy to control the number of each kind of ant during the searching process. In addition, ACE does not employ the construction graph usually employed by classical ACO algorithms. Instead, the search is performed using a state space exploration approach. This paper studies the performance of ACE in the context of the Travelling Salesman Problem (TSP), a classical combinatorial optimisation problem. The results are compared with the results of two well known ACO algorithms: ACS and MMAS. ACE shows better performance than ACS and MMAS in almost every TSP tested instance.