Journal ArticleDOI
Ant-based load balancing in telecommunications networks
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TLDR
A novel method of achieving load balancing in telecommunications networks using ant-based control, which is shown to result in fewer call failures than the other methods, while exhibiting many attractive features of distributed control.Abstract:
This article describes a novel method of achieving load balancing in telecommunications networks. A simulated network models a typical distribution of calls between nodes; nodes carrying an excess ...read more
Citations
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Journal ArticleDOI
Ant colony system: a cooperative learning approach to the traveling salesman problem
TL;DR: The results show that the ACS outperforms other nature-inspired algorithms such as simulated annealing and evolutionary computation, and it is concluded comparing ACS-3-opt, a version of the ACS augmented with a local search procedure, to some of the best performing algorithms for symmetric and asymmetric TSPs.
Book
Ant Colony Optimization
TL;DR: Ant colony optimization (ACO) is a relatively new approach to problem solving that takes inspiration from the social behaviors of insects and of other animals as discussed by the authors In particular, ants have inspired a number of methods and techniques among which the most studied and the most successful is the general purpose optimization technique known as ant colony optimization.
Journal ArticleDOI
Ant algorithms for discrete optimization
TL;DR: An overview of recent work on ant algorithms, that is, algorithms for discrete optimization that took inspiration from the observation of ant colonies' foraging behavior, and the ant colony optimization (ACO) metaheuristic is presented.
Book ChapterDOI
Ant Colony Optimization
TL;DR: Ant Colony Optimization (ACO) is a stochastic local search method that has been inspired by the pheromone trail laying and following behavior of some ant species as discussed by the authors.
Journal ArticleDOI
Ant colony optimization: artificial ants as a computational intelligence technique
TL;DR: The introduction of ant colony optimization (ACO) is discussed and all ACO algorithms share the same idea and the ACO is formalized into a meta-heuristics for combinatorial problems.
References
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Book
Nonparametric statistics for the behavioral sciences
TL;DR: This is the revision of the classic text in the field, adding two new chapters and thoroughly updating all others as discussed by the authors, and the original structure is retained, and the book continues to serve as a combined text/reference.
Journal ArticleDOI
A note on two problems in connexion with graphs
TL;DR: A tree is a graph with one and only one path between every two nodes, where at least one path exists between any two nodes and the length of each branch is given.
Journal ArticleDOI
Ant system: optimization by a colony of cooperating agents
TL;DR: It is shown how the ant system (AS) can be applied to other optimization problems like the asymmetric traveling salesman, the quadratic assignment and the job-shop scheduling, and the salient characteristics-global data structure revision, distributed communication and probabilistic transitions of the AS.
Journal ArticleDOI
La reconstruction du nid et les coordinations interindividuelles chezBellicositermes natalensis etCubitermes sp. la théorie de la stigmergie: Essai d'interprétation du comportement des termites constructeurs
TL;DR: A reconstruction of Cubi termes natalensis, a review of the building blocks of the Cuban legal system, and some of the strategies used to achieve this goal are described.
Proceedings Article
The dynamics of collective sorting robot-like ants and ant-like robots
Jean-Louis Deneubourg,Simon Goss,Nigel R. Franks,Ana B. Sendova-Franks,Claire Detrain,L. Chrétien +5 more
TL;DR: A distributed sorting algorithm, inspired by how ant colonies sort their brood, is presented for use by robot teams, offering the advantages of simplicity, flexibility and robustness.