Abstract
Common Service Centers (CSCs), which are also known as Tele-centers and Rural Kiosks, are important infrastructural options for any country aiming to provide E-Governance services in rural regions. Their main objective is to provide adequate information and services to a country’s rural areas, thereby increasing government-citizen connectivity. Within developing nations, such as India, many CSC allocations are being planned. This study proposes a solution for allocating a CSC for villages in a country according to their E-Governance plan. The Fuzzy C-Means (FCM) algorithm was used for clustering the village dataset and finding a cluster center for CSC allocation, and the Particle Swarm Optimization (PSO) algorithm was used for further optimizing the results obtained from the FCM algorithm based on population. In the context of other studies addressing similar issues, this study highlights the practical implementation of location modeling and analysis. An extensive analysis of the results obtained using a village dataset from India including four prominent states shows that the proposed solution reduces the average traveling costs of villagers by an average of 33 % compared with those of allocating these CSCs randomly in a sorted order and by an average of 11 % relative to centroid allocation using the FCM-based approach only. As compared to traditional approaches like P-Center and P-Median, the proposed scheme is better by 31 % and 14 %, respectively. Therefore, the proposed algorithm yields better results than classical FCM and other types of computing techniques, such as random search & linear programming. This scheme could be useful for government departments managing the allocation of CSCs in various regions. This work should also be useful for researchers optimizing the location allocation schemes used for various applications worldwide.
Similar content being viewed by others
References
Altinel IK, Durmaz E, Aras N, Özkisacik KC (2009) A location–allocation heuristic for the capacitated multi-facility Weber problem with probabilistic customer locations. Eur J Oper Res 198(3):790–799
Amin SH, Zhang G (2013) A multi-objective facility location model for closed-loop supply chain network under uncertain demand and return. Appl Math Model 37(6):4165–4176
Arabani AB, Farahani RZ (2012) Facility location dynamics: An overview of classifications and applications. Comput Ind Eng 62(1):408–420
Arbelaitz O, Gurrutxaga I, Muguerza J, Pérez JM, Perona I (2013) An extensive comparative study of cluster validity indices. Pattern Recogn 46(1):243–256
Arc GIS resource center (2015) Location-allocation analysis, What is location-allocation. Accessed from Link: http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html#//004700000050000000 on 5 th May, 2015
Arifin MS (2011) Location allocation problem using genetic algorithm and simulated annealing. A case study based on school in Enschede. Master Thesis, Enschede
Asik O (2014) Location Optimization To Determine Telecenter Network In Rural Turkey. Doctoral Dissertation, Cornell University. Accessed from http://dspace.library.cornell.edu/handle/1813/36029 on 15 th December 2015
Bender T, Hennes H, Kalcsics J, Melo MT, Nickel S (2002) Location software and interface with GIS and supply chain management. Facility location: Applications and theory 233–274
Bezdek JC (1981) Models for pattern recognition In: Pattern recognition with fuzzy objective function algorithms, 1-13. US: Springer
Bhattacharya U, Tiwari RN (1994) Imprecise weights in Weber facility location problem. Fuzzy Sets Syst 62(1):31–38
Bhattacharya U, Rao JR, Tiwari RN (1993) Bi-criteria multi facility location problem in fuzzy environment. Fuzzy Sets Syst 56(2):145–153
Biswal B, Dash PK, Panigrahi BK (2009) Power quality disturbance classification using fuzzy C-means algorithm and adaptive particle swarm optimization. IEEE Trans Ind Electron 56(1):212–220
Brandeau ML, Chiu SS (1989) An overview of representative problems in location research. Manag Sci 35 (6):645–674
Carlisle A, Dozier G (2000) Adapting particle swarm optimization to dynamic environments In: Proceedings of the International Conference on Artificial Intelligence Vol. 1, 429-434. Athens, GA, USA: CSPlEA Press
Castillo O, Rubio E, Soria J, Naredo E (2012) Optimization of the Fuzzy C-Means Algorithm using Evolutionary Methods. Eng Lett 20(1):EL_20_1_08
Chen CT (2001) A fuzzy approach to select the location of the distribution center. Fuzzy Sets Syst 118 (1):65–73
Choudhury J, Ghosh R (2015) E-Governance and Rural Development: An Assessment of CSCS in Tripura. IBMRD’s J Manag Res 4(1):18–29
Christaller W (1933) Die zentralenorte in Suddeutschland. Gustav Fischer, Jena, Germany. Translated by Baskin CW (1966) as Central places in Southern Germany
Church RL (1999) Location modelling and GIS. Geogr Inf Syst 1:293–303
Church RL (2002) Geographical information systems and location science. Comput Oper Res 29(6):541–562
Clerc M (2006) Stagnation analysis in particle swarm optimization or what happens when nothing happens. Technical Report, UK: Sussex Online available at. http://cswww.essex.ac.uk/technical-reports/2006/csm-460.pdf
Curtin KM, Hayslett-McCall K, Qiu F (2010) Determining optimal police patrol areas with maximal covering and backup covering location models. Networks and Spatial Economics 10(1):125–145
Dass R, Bhattacherjee A (2011) Status of Common Service Center Program in India: Issues, Challenges and Emerging Practices for Rollout (No. WP2011-02-03). Research report, India: Indian Institute of Management Ahmedabad
Datta K, Saxena A (2013) Developing entrepreneurship and e-government in India: Role of common service centers. J E-Governance 36(2):92–100
de Oliveira JV, Pedrycz W (2007) Advances in fuzzy clustering and its applications. Wiley, New York. Pg-9
Densham PJ (1994) Integrating GIS and spatial modelling: visual interactive modelling and location selection. Geogr Syst 1(3):203–219
Döring C., Lesot MJ, Kruse R (2006) Data analysis with fuzzy clustering methods. Comput Stat Data Anal 51(1):192–214
Eberhart RC, Shi Y (2001) Tracking and optimizing dynamic systems with particle swarms In: Evolutionary Computation, 2001, Proceedings of the 2001 IEEE Congress (1), 94–100
Emami MR, Goldenberg A (1996) An improved fuzzy modeling algorithm II - System identification In: Fuzzy Information Processing Society, 1996, NAFIPS, 1996 Biennial Conference of the North American, IEEE, 294–298
Francis RL, McGinnis LF, White JA (1983) Locational analysis. Eur J Oper Res 12(3):220–252
Gilli M, Winker P (2009) Heuristic optimization methods in econometrics. Handbook of computational econometrics, pp. 81–119
Goel L, Gupta D, Panchal VK (2012) Hybrid bio-inspired techniques for land cover feature extraction: A remote sensing perspective. Appl Soft Comput 12(2):832–849
Goodchild MF, Longley PA, Maguire DJ, Rhind DW (2005) Geographic information systems and science 2. Wiley, Chichester
Gupta DS, Kaushal S (n.d.) Towards an Open Government, E-Governance Infrastructure-Status and Challenges. Case Study on Himachal Pradesh, National Information Center, Government of Himachal Pradesh, India. Accessed on 15th March, 2015 from http://himachal.gov.in/WriteReadData/l892s/17_l892s/eGovPaper-Network-2012-11500815.pdf
Hamacher HW, Drezner Z (2002) Facility location: applications and theory. Science & Business Media: Springer
Hamacher HW, Nickel S (1998) Classification of location models. Locat Sci 6(1):229–242
Harper PR, Shahani AK, Gallagher JE, Bowie C (2005) Planning health services with explicit geographical considerations: a stochastic location–allocation approach. Omega 33 (2):141–152
Hassan R, Cohanim B, De Weck O, Venter G (2005) A comparison of particle swarm optimization and the genetic algorithm In: Proceedings of the 1st AIAA multidisciplinary design optimization specialist conference, 1–13
Heeks R (2002) Information Systems and Developing Countries: Failure, Success, and Local Improvisations. Inf Soc 18(2):101–112
Hotelling H (1929) Stability in competition. Economic Journal 39:41–57. Accessed from:http://www.slideshare.net/sppatel06/common-service-center-unlocking-the-potential-of-rural-india on 7th June, 2015
Hu TL (2003) A fuzzy-based customer classification method for demand-responsive logistical distribution operations. Fuzzy Set Syst 139(2):431–450
Kennedy J, Eberhart R (1990) Particle Swarm Optimization In: Proceedings of the IEEE International Conference on Neural Networks, Perth, Australia, 1942–1945
Klose A, Drexl A (2005) Facility location models for distribution system design. Eur J Oper Res 162 (1):4–29
Kolokolov AA, Zaozerskaya LA (2013) Solving a bicriteria problem of optimal service centers location. J Math Modelling Algorithms Operations Res 12(2):105–116
Kolokolov AA, Zaozerskaya LA (2006) A Bicriteria problem of optimal service centers location In: Proceedings of 12th IFAC International Symposium III, St, Etienne: France, 429– 434
Konar A (2006) Computational intelligence: principles, techniques and applications. Science & Business Media: Springer
Kucukdeniz T, Baray A, Ecerkale K, Esnaf S (2012) Integrated use of fuzzy c-means and convex programming for capacitated multi-facility location problem. Expert Systems with Applications 39(4):4306–4314
Kumar S, Kumar S (2002) Methods for community participation: a complete guide for practitioners. Methods for community participation: a complete guide for practitioners
Lau E (2003) Challenges for e-government development In: 5th Global Forum on reinventing Government, 1–18
Le Hoang Son PLL, Cuong BC, Hung HA (2012) Data mining in GIS: a novel context-based fuzzy geographically weighted clustering algorithm. International Journal of Machine Learning and Computing 2(3):235–238
Liu N, Huang B, Chandramouli M (2006) Optimal siting of fire stations using GIS and ANT algorithm. J Comput Civ Eng 20(5):361–369
Losch A (1940) Die raumlicheOrdnung der Wirtschaft (English translation, 2nd edn., G. Fischer, 1954, The Economics of Location). Yale University Press: New Haven
Misra H, Hiremath BN (2006) ICT Initiatives for Sustainable Livelihood Security: A Demand-driven Rural E-governance Framework for Scale-up. Institute of Rural Management Anand: Gujarat, India
Mousa AA, El-Shorbagy MA, Abd-El-Wahed WF (2012) Local search based hybrid particle swarm optimization algorithm for multi-objective optimization. Swarm Evol Comput 3 :1–14
Murray AT (2005) Geography in coverage modeling: exploiting spatial structure to address complementary partial service of areas. Ann Assoc Am Geogr 95(4):761–772
Murray AT (2008) Economic geography: location theory. In lessons from a survey in four states. Rev Mark Integr 5 (1):1–42
Murray AT (2010) Advances in location modeling: GIS linkages and contributions. J Geogr Syst 12(3):335–354
Murray AT, Church RL (2009) Business Site Selection. Location Analysis and GIS. Book Tools
Naik G, Joshi S, Basavarajappa KP (2010) Making E-Governance centers financially sustainable in rural India: A conceptual design for action research, Working Research Paper 317 IIM. Bangalore, India
Niu Q, Huang X (2011) An improved fuzzy C-means clustering algorithm based on PSO. J Softw 6 (5):873–879
Owen SH, Daskin MS (1998) Strategic facility location: A review. Eur J Oper Res 111(3):423–447
Parkash C (2012) Common Services Centers (CSC) Scheme. TRAI Report Telecom Regulatory Authority of India, India
Poli R, Kennedy J, Blackwell T (2007) Particle Swarm Optimization. Swarm Intell 1(1):33–57
Prasad K (2012) E-Governance Policy for Modernizing Government through Digital Democracy in India. J Inf Policy 2:183–203
Rahman SU, Smith DK (2000) Use of location-allocation models in health service development planning in developing nations. Eur J Oper Res 123(3):437–452
Revelle CS, Eiselt HA, Daskin MS (2008) A bibliography for some fundamental problem categories in discrete location science. Eur J Oper Res 184(3):817–848
ReVelle DO (2004) Recent advances in bolide entry modeling: A bolide potpourri. Earth, Moon, and Planets 95(1-4):441– 476
Ribeiro A, Antunes AP (2002) A GIS-based decision-support tool for public facility planning. Environ Plann B 29(4):553– 570
Ruspini EH (1970) Numerical methods for fuzzy clustering. Inf Sci 2(3):319–350
Shadrach MB, Sharma ITU (2013) Impact assessment of Indian common services centres. Ministry Report, Ministry of Communication and Information Technology. Government of India, New Delhi
Shourijeh MT, Kermanshah M, Mamdoohi AR, Faghri A, Hamad K (2012) A Mathematical Optimization Model for Locating Telecenters. Appl Math 3(3):251–263
Syam SS, Côté MJ (2010) A location–allocation model for service providers with application to not-for-profit health care organizations. Omega 38(3):157–166
Ting CJ, Chen CH (2013) A multiple ant colony optimization algorithm for the capacitated location routing problem. Int J Prod Econ 141(1):34–44
Ting CJ, Wu KC, Chou H (2014) Particle swarm optimization algorithm for the berth allocation problem. Expert Syst Appl 41(4):1543–1550
Tlili T, Faiz S, Krichen S (2014) A hybrid meta-heuristic for the distance-constrained capacitated vehicle routing problem. Procedia Soc Behav Sci 109:779–783
Tzeng GH, Chen YW (1999) The optimal location of airport fire stations: a fuzzy multi-objective programming and revised genetic algorithm approach. Transp Plan Technol 23(1):37–55
Varma A, Shubha V (2009) Common Services Centers Scheme. IL & FS Accessed from http://csc.gov.in/index.php?option=com_csc&layout=download&f=February2009-Anniversary_issue.pdf&Itemid=335 on 20th August 2015
Vengurlekar N (n.d.) Common Service Centers. IL & FS, Accessed from http://www.ilfsindia.com/downloads/bus_concept/CSC_ILFS_website.pdf on 15th October, 2015
Vijay R, Gupta A, Kalamdhad AS, Devotta S (2005) Estimation and allocation of solid waste to bin through geographical information systems. Waste Manag Res 23(5):479–484
Watson-Gandy CDT (1982) Heuristic procedures for the m-partial cover problem on a plane. Eur J Oper Res 11(2):149– 157
Xifeng T, Ji Z, Peng X (2013) A multi-objective optimization model for sustainable logistics facility location. Transp Res Part D: Transp Environ 22:45–48
Yang L, Jones BF, Yang SH (2007) A fuzzy multi-objective programming for optimization of fire station locations through genetic algorithms. Eur J Oper Res 181(2):903–915
Yang L, Sun X, Chi T (2013) An ant colony optimization algorithm and multi-agent system combined method to solve Single Source Capacitated Facility Location Problem Advanced Computational Intelligence (ICACI), 2013 Sixth International Conference, IEEE, 102–105
Yong Y, Chongxun Z, Pan L (2004) A novel fuzzy c-means clustering algorithm for image thresholding. Meas Sci Rev 4(1):11–19
Author information
Authors and Affiliations
Corresponding author
Appendix A: Raw Data
Appendix A: Raw Data
Rights and permissions
About this article
Cite this article
Gupta, R., Muttoo, S.K. & Pal, S.K. Fuzzy C-Means Clustering and Particle Swarm Optimization based scheme for Common Service Center location allocation. Appl Intell 47, 624–643 (2017). https://doi.org/10.1007/s10489-017-0917-0
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10489-017-0917-0