Name
Title | ||
|---|---|---|
A deterministic metaheuristic approach using "logistic ants" for combinatorial optimization |
Abstract | ||
|---|---|---|
Ant algorithms are usually derived from a stochastic modeling based on some specific probability laws. We consider in this paper a full deterministic model of "logistic ants" which uses chaotic maps to govern the behavior of the artificial ants. We illustrate and test this approach on a TSP instance, and compare the results with the original Ant System algorithm. This change of paradigm--deterministic versus stochastic--implies a novel view of the internal mechanisms involved during the searching and optimizing process of ants. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-15461-4_30 | ANTS Conference |
Keywords | Field | DocType |
stochastic modeling,optimizing process,full deterministic model,novel view,chaotic map,tsp instance,logistic ant,internal mechanism,artificial ant,deterministic metaheuristic approach,ant algorithm,combinatorial optimization,stochastic model,metaheuristics,swarm intelligence,optimization | Ant colony optimization algorithms,Mathematical optimization,Parallel metaheuristic,Computer science,Swarm intelligence,Combinatorial optimization,Deterministic system,Artificial intelligence,Chaotic,Machine learning,Artificial Ants,Metaheuristic | Conference |
Volume | ISSN | ISBN |
6234 | 0302-9743 | 3-642-15460-3 |
Citations | PageRank | References |
3 | 0.40 | 4 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rodolphe Charrier | 1 | 16 | 2.42 |
| Christine Bourjot | 2 | 102 | 13.97 |
| François Charpillet | 3 | 448 | 54.11 |