Modeling of territorial community formation as a graph partitioning problem

Authors

DOI:

https://doi.org/10.15587/1729-4061.2016.60848

Keywords:

graph partitioning, genetic algorithm, NP-complete problem, territorial community, settlement

Abstract

The territorial community formation process as a graph partitioning problem is considered. The main goal of territorial community formation is to reduce the budget and save public funds. The formation process of communities where settlements, which make up the community, have an administrative building, healthcare institution, high school, kindergarten is investigated. Additional restrictions are imposed on these indicators for uniform distribution of the region's population and community incomes. The minimum distance from the community center to other settlements is taken as a function of the goal of territorial community formation. The mathematical model of this problem, which is a modified graph partitioning problem is developed. The modification lies in using specific constraints arising from the problem statement. The notion of independence of communities and adjacency of individual councils is introduced to build efficient territorial community formation algorithms. This allowed us to formalize the problem from a mathematical point of view. In turn, this made it possible to develop an algorithm for solving this problem, which is to use genetic algorithms to solve the existing problem. The developed model and algorithm of territorial community formation are tested. According to the expert group on the TC formation, the resulting solution showed satisfactory results.

Author Biographies

Василь Володимирович Литвин, National University "Lviv Polytechnic" 12 S. Bandery str., Lvіv, Ukraine, 79013

Doctor of Technical Sciences, professor

Department of Information Systems and Networks

Дмитро Ілліч Угрин, Chernivtsi Department of National Technical University 'Kharkiv Polytechnic Institute' 203A Holovna str., Chernivtsi, Ukraine, 58000

PhD, associate professor

Department of Information Systems 

Андріан Мирославович Фітьо, National University "Lviv Polytechnic" 12 S. Bandery str., Lvіv, Ukraine, 79013

Department of Information Systems and Networks

References

  1. Zakon Ukrai'ny Pro dobrovil'ne ob’jednannja terytorial'nyh gromad. Available at: http://zakon5.rada.gov.ua/laws/show/157-19
  2. Yevstignyeev, V. A. (1985). Application of graph theory in programming. Moscow: Nauka, 352.
  3. Swami, M., Thulasiraman, K. (1984). Graphs, Networks and Algorithms. Moscow: Nauka, 256.
  4. Lytvyn, V., Shakhovska, N., Pasichnyk, V., Dosyn, D. (2012). Searching the Relevant Precedents in Dataspaces Based on Adaptive Ontology. Computational Problems of Electrical Engineering, 2 (1), 75–81.
  5. Dosyn, D., Lytvyn, V. (2012). Planning of Intelligent Diagnostics Systems Based Domain Ontology. The VIIIth International Conference Perspective Technologies and Methods in MEMS Design, Polyana, Ukraine, 103.
  6. Lytvyn, V., Dosyn, D., Medykovskyj, M., Shakhovska, N. (2011). Intelligent agent on the basis of adaptive ontologies construction. Signal Modelling Control. Available at: http://it.p.lodz.pl/
  7. Montes-y-Gómez, M., Gelbukh, A., López-López, A. (2000). Comparison of Conceptual Graphs. Lecture Notes in Artificial Intelligence, 1793, 548–556. doi: 10.1007/10720076_50
  8. Lytvyn, V. (2013) Design of intelligent decision support systems using ontological approach. An international quarterly journal on economics in technology, new technologies and modelling processes, 2 (1), 31–38.
  9. Feldmann, A., Foschini, L. (2012). Balanced Partitions of Trees and Applications. Proceedings of the 29th International Symposium on Theoretical Aspects of Computer Science, 100–111.
  10. Alzate, C., Suykens, J. A. K. (2010). Multiway Spectral Clustering with Out-of-Sample Extensions through Weighted Kernel PCA. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32 (2), 335–347. doi: 10.1109/tpami.2008.292
  11. Kurve, N., Griffin, J., Kesidis, A. (2011). A graph partitioning game for distributed simulation of networks. Proceedings of the 2011 International Workshop on Modeling, Analysis, and Control of Complex Networks, 9–16.
  12. Chevalier, C., Pellegrini, F. (2008). PT-Scotch: A tool for efficient parallel graph ordering. Parallel Computing, 34 (6-8), 318–331. doi: 10.1016/j.parco.2007.12.001
  13. Meyerhenke, H. (2013). Shape Optimizing Load Balancing for MPI-Parallel Adaptive Numerical Simulations. 10th DIMACS Implementation Challenge on Graph Partitioning and Graph Clustering, 67–82.
  14. Meyerhenke, H., Monien, B., Sauerwald, T. (2009). A new diffusion-based multilevel algorithm for computing graph partitions. Journal of Parallel and Distributed Computing, 69 (9), 750–761. doi: 10.1016/j.jpdc.2009.04.005

Published

2016-02-27

How to Cite

Литвин, В. В., Угрин, Д. І., & Фітьо, А. М. (2016). Modeling of territorial community formation as a graph partitioning problem. Eastern-European Journal of Enterprise Technologies, 1(4(79), 47–52. https://doi.org/10.15587/1729-4061.2016.60848

Issue

Section

Mathematics and Cybernetics - applied aspects