Meta-heuristic algorithms to improve fuzzy C-means and K-means clustering for location allocation of telecenters under e-governance in developing nationsSaibal K. Pal
, Rajan Gupta
, Sunil K. Muttoo
, 2019, izvirni znanstveni članek
Opis: 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.
Najdeno v: ključnih besedah
Povzetek najdenega: ...(particle swarm optimization, bat algorithm, and ant colony optimization) for the improvement of traditional clustering...
Ključne besede: ant colony optimization, bat algorithm, common service center, e-governance, fuzzy clustering, meta-heuristic algorithm, particle swarm optimization
Objavljeno: 01.04.2021; Ogledov: 785; Prenosov: 3
Polno besedilo (0,00 KB)
Gradivo ima več datotek! Več...