Evaluation of the quality of the ”Montecarlo plus K-means” heuristics using benchmark functions
The evaluation in terms of quality of the results obtained from the use of a heuristic method is necessary to, first, verify the obtained results since heuristic methods do not guarantee to reach the optimum because all the possibilities are not fully explored. Secondly, it becomes interesting to va...
Guardado en:
| Autores principales: | , , , |
|---|---|
| Formato: | Objeto de conferencia |
| Lenguaje: | Inglés |
| Publicado: |
2020
|
| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/104772 |
| Aporte de: |
| Sumario: | The evaluation in terms of quality of the results obtained from the use of a heuristic method is necessary to, first, verify the obtained results since heuristic methods do not guarantee to reach the optimum because all the possibilities are not fully explored. Secondly, it becomes interesting to validate such method, thus granting a high-quality index. Through our proposal, starting on the analysis of the literature survey on many optimization test functions, we are proposing the evaluation of a heuristic method based on Montecarlo approaches in conjunction with K-means clustering. Besides this, we aim to evaluate the results obtained through the use of some complex optimization test functions. Also, we seek to add a defined quality index to the original heuristic method relying on the consequent improvement in the results. As a side-work, we would aim to validate the heuristic mentioned aboveand optimize the algorithm in terms of scalability and quality. |
|---|