Use of Ant Colony Optimization Algorithm for Determining Traveling Salesman Problem Routes
Ant Colony Optimization is one of the meta-heuristic methods used to solve combinatorial optimization problems that are quite difficult. Ant Colony Optimization algorithm is inspired by ant behavior in the real world to build the shortest path between food sources and their nests. Traveling Salesman...
Guardado en:
| Autores principales: | , , |
|---|---|
| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Department of Mathematics, UIN Sunan Ampel Surabaya
2019
|
| Materias: | |
| Acceso en línea: | https://doaj.org/article/744e312ec332472a883752ceacfcf3c5 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| Sumario: | Ant Colony Optimization is one of the meta-heuristic methods used to solve combinatorial optimization problems that are quite difficult. Ant Colony Optimization algorithm is inspired by ant behavior in the real world to build the shortest path between food sources and their nests. Traveling Salesman Problem is a problem in optimization. Traveling Salesman Problem is a problem to find the minimum distance from the initial node to the whole node with each node must be visited exactly once and must return to the initial node. Traveling Salesman Problem is a non-deterministic polynomial-time complete problem. This research discusses the solution of the Traveling Salesman Problem using the Ant Colony Optimization algorithm and also using the exact algorithm. The results showed that the greater the size of the Traveling Salesman Problem case, the longer the execution time required. The results also showed that the execution times of the Ant Colony Optimization are much faster than the execution time of the exact method. |
|---|