Abordagem heurística baseada em busca em vizinhança variável para o agrupamento balanceado de dados pelo critério da soma mínima das distâncias quadráticas
After advances in collecting and storing data and the growth in applications that provide new information, the number of data elements available is huge in both volume and variety. With this increase in the quantity of information, the need to understand them and summarize them has become increas...
Spremljeno u:
| Glavni autor: | |
|---|---|
| Daljnji autori: | |
| Format: | Dissertação |
| Jezik: | por |
| Izdano: |
Brasil
|
| Teme: | |
| Online pristup: | https://repositorio.ufrn.br/jspui/handle/123456789/21976 |
| Oznake: |
Dodaj oznaku
Bez oznaka, Budi prvi tko označuje ovaj zapis!
|
| Sažetak: | After advances in collecting and storing data and the growth in applications that provide
new information, the number of data elements available is huge in both volume and
variety. With this increase in the quantity of information, the need to understand them and
summarize them has become increasingly urgent. The Balanced Clustering seeks to find
groups of similar entities that have approximately the same size. In this dissertation, we
propose a new heuristic approach based on metaheuristic Variable Neighborhood Search
(VNS) and methodology "Less is More Approach"(LIMA) to data clustering problem
using the criterion of the minimum sum-of-squared distances applying balancing restriction
for the groups. The algorithms found in the literature are not scalable, while the
problem of increased size in addition to elements 5000 in accordance with experiments
performed in this study. The computational experiments show that the proposed method
outperforms the current state of the art for the problem. |
|---|