International Journal of Fuzzy Logic and Intelligent Systems 2019; 19(4): 290-298
Published online December 25, 2019
https://doi.org/10.5391/IJFIS.2019.19.4.290
© The Korean Institute of Intelligent Systems
Rajan Gupta1, Sunil Kumar Muttoo1, and Saibal K. Pal2
1Department of Computer Science, University of Delhi, India
2SAG Lab, Defence Research & Development Organization (DRDO), Delhi, India
Correspondence to :
Rajan Gupt (Guptarajan2000@gmail.com)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
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.
Keywords: Ant colony optimization, Bat algorithm, Common service center, E-governance, Fuzzy clustering, Meta-heuristic algorithm, Particle swarm optimization, Rural kiosk
E-mail: guptarajan2000@gmail.com
E-mail: drskmuttoo@gmail.com
Email: skptech@yahoo.com
International Journal of Fuzzy Logic and Intelligent Systems 2019; 19(4): 290-298
Published online December 25, 2019 https://doi.org/10.5391/IJFIS.2019.19.4.290
Copyright © The Korean Institute of Intelligent Systems.
Rajan Gupta1, Sunil Kumar Muttoo1, and Saibal K. Pal2
1Department of Computer Science, University of Delhi, India
2SAG Lab, Defence Research & Development Organization (DRDO), Delhi, India
Correspondence to:Rajan Gupt (Guptarajan2000@gmail.com)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
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.
Keywords: Ant colony optimization, Bat algorithm, Common service center, E-governance, Fuzzy clustering, Meta-heuristic algorithm, Particle swarm optimization, Rural kiosk
Overall conceptualization of the optimization of the telecenter in the search space.
Table 1 . Cost comparison for various techniques implemented standalone and in combination for different regions.
Algorithm | R1 | R2 | R3 | R4 | Total |
---|---|---|---|---|---|
KM-R | 33825 | 45835 | 39990 | 20109 | 139759 |
KM-C | 23465 | 24957 | 30234 | 16784 | 95440 |
FCM-R | 32788 | 44830 | 38997 | 20023 | 136639 |
FCM-C | 22996 | 23981 | 29092 | 15971 | 92042 |
FCM-PSO | 21870 | 22317 | 28454 | 13189 | 85832 |
FCM-Bat | 20727 | 19665 | 26627 | 12816 | 79837 |
FCM-ACO | 21124 | 20785 | 27632 | 12980 | 82521 |
P-center | 68470 | 45120 | 39018 | 14065 | 166673 |
P-median | 22770 | 25010 | 38990 | 14580 | 101350 |
Table 2 . Statistical measures of techniques for total cost of four regions over repeated experimentation (approx. values).
FCM-PSO | FCM-Bat | FCM-ACO | |
---|---|---|---|
Mean | 21458 | 20047 | 21004 |
Standard deviation | 6205 | 6104 | 6139 |
Minimum | 20100 | 19649 | 200455 |
Maximum | 24623 | 22432 | 23985 |
Range | 4523 | 2783 | 3940 |
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International Journal of Fuzzy Logic and Intelligent Systems 2021; 21(4): 378-390 https://doi.org/10.5391/IJFIS.2021.21.4.378Overall conceptualization of the optimization of the telecenter in the search space.