Name
Abstract | ||
|---|---|---|
Abstract Recently we proposed an application of ant colony optimization (ACO) to simulate socio-cognitive features of a population, incorporating perspective-taking ability to generate differently acting ant colonies. Although our main goal was simulation, we took advantage of the fact that the quality of the constructed system was evaluated based on selected traveling salesman problem instances, and the resulting computing system became a metaheuristic, which turned out to be a promising method for solving discrete problems. In this paper, we extend the initial sets of populations driven by different perspective-taking inspirations, seeking both optimal configuration for solving a number of TSP benchmarks, at the same time constituting a tool for analyzing socio-cognitive features of the individuals involved. The proposed algorithms are compared against classic ACO, and are found to prevail in most of the benchmark functions tested. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.jocs.2016.10.010 | Journal of Computational Science |
Keywords | Field | DocType |
Ant-colony optimization,Discrete optimization,Socio-cognitive inspirations,Metaheuristics,Agent-based simulation | Ant colony optimization algorithms,Population,Mathematical optimization,Parallel metaheuristic,Discrete optimization,Computer science,Travelling salesman problem,Artificial intelligence,Ant colony,Computing systems,Metaheuristic | Journal |
Volume | ISSN | Citations |
21 | 1877-7503 | 4 |
PageRank | References | Authors |
0.43 | 16 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aleksander Byrski | 1 | 269 | 45.03 |
| Ewelina Swiderska | 2 | 6 | 1.18 |
| Jakub Lasisz | 3 | 6 | 1.18 |
| Marek Kisiel-Dorohinicki | 4 | 274 | 42.43 |
| Tom Lenaerts | 5 | 276 | 53.44 |
| Dana Samson | 6 | 18 | 3.01 |
| Bipin Indurkhya | 7 | 193 | 51.14 |
| Ann Nowé | 8 | 971 | 123.04 |