20.500.12556/RUNG-6394
Meta-heuristic algorithms to improve fuzzy C-means and K-means clustering for location allocation of telecenters under e-governance in developing nations
The telecenter, popularly known as the rural kiosk or common service center, is an important building block for the improvement of e-governance in developing nations as they help in better citizen engagement. Setting up of these centers at appropriate locations is a challenging task; inappropriate locations can lead to a huge loss to the government and allied stakeholders. This study proposes the use of various meta-heuristic algorithms (particle swarm optimization, bat algorithm, and ant colony optimization) for the improvement of traditional clustering approaches (K-means and fuzzy C-means) used in the facility location allocation problem and maps them for the betterment of telecenter location allocation. A dataset from the Indian region was considered for the purpose of this experiment. The performance of the algorithms when applied to traditional facility location allocation problems such as set-cover, P-median, and the P-center problem was investigated, and it was found that their efficiency improved by 20%–25% over that of existing algorithms.
ant colony optimization
bat algorithm
common service center
e-governance
fuzzy clustering
meta-heuristic algorithm
particle swarm optimization
true
true
false
Angleški jezik
Ni določen
Neznano
2021-03-31 23:29:00
2021-04-01 08:33:49
2023-06-09 03:43:01
0000-00-00 00:00:00
2019
0
0
str. 290-298
no. 4
Vol. 19
2019
0000-00-00
NiDoloceno
NiDoloceno
NiDoloceno
0000-00-00
0000-00-00
0000-00-00
57967619
004
2093-744X
10.5391/IJFIS.2019.19.4.290
URN:SI:UNG:REP:LKE8DYU1
http://doi.org/10.5391/IJFIS.2019.19.4.290
1
https://repozitorij.ung.si/Dokument.php?lang=slv&id=21831
Univerza v Novi Gorici
0
2
0