SHORTEST PATH DETERMINATION BETWEEN EDUCATIONAL INSTITUTIONS OF RĒZEKNE MUNICIPALITY

Authors

  • Pēteris Grabusts Rezekne Academy of Technologies (LV)
  • Jurijs Musatovs Rezekne Academy of Technologies (LV)

DOI:

https://doi.org/10.17770/sie2017vol3.2386

Keywords:

Educational institutions, Optimization, Rēzekne Municipality, Simulated Annealing', Travelling Salesman Problem

Abstract

This study describes an optimization method called Simulated Annealing. The Simulated Annealing method is widely used in various combinatorial optimization tasks. Simulated Annealing is a stochastic optimization method that can be used to minimize the specified cost function given a combinatorial system with multiple degrees of freedom. In this study the application of the Simulated Annealing method to a well - known task of combinatorial analysis, Travelling Salesman Problem, is demonstrated and an experiment aimed to find the shortest tour distances between educational institutions of Rēzekne Municipality is performed. It gives possibilities to analyze and search optimal schools' network in Rēzekne Municipality.

References

Applegate, D.L., Bixby, R., Chvátal, V., Cook, W. (2006). The Traveling Salesman Problem: A Computational Study. Princeton University Press.

Cook, W. (2011). In Pursuit of the Traveling Salesman. Princeton: Princeton University Press, USA.

Coughlin, J.P., Baran, R.H. (1985). Neural Computation in Hopfield Networks and Boltzmann Machines. University of Delaware Press.

Educational institutions. (2016, December 29). Retrieved from http://rezeknesnovads.lv/novada-iestades/izglitiba/izglitibas-iestades/ (in Latvian).

Grabusts, P. (2000). Solving TSP using classical simulated annealing method. Scientific Proceedings of Riga Technical University: Computer Science. Information Technology and Management Science, RTU, Riga, Issue 5, Volume 2, pp. 32-39.

Granville, V., Krivanek, M., Rasson J-P. (1994). Simulated annealing: A proof of convergence. IEEE Transactions on Pattern Analysis and Machine Intelligence, 16(6), pp. 652–656.

Ingber, L. (1993). Simulated annealing: Practice versus theory. Math. Comput. Modelling, 18, pp. 29–57.

Kirkpatrick, S., Gelatt, C.D., Vecchi, M.P. (1983). Optimization by Simulated Annealing. Science, vol. 220, pp. 671-680.

Kuzmina, I. (2016, December 29). Ideālais skolu tīkls negatavs un slepens. Latvijas avīze. Retrieved from http://www.la.lv/idealais-skolu-tikls-negatavs-un-slepens/ (in Latvian).

Laarhoven, P.J.M., Aarts, E.H.L. (1987). Simulated Annealing: Theory and Applications. D.Reidel Publishing Company, Holland.

Otten, R.H., Ginneken, L.P. (1989). The Annealing Algorithm. Kluwer Academic Publishers.

Downloads

Published

2017-05-26

How to Cite

Grabusts, P., & Musatovs, J. (2017). SHORTEST PATH DETERMINATION BETWEEN EDUCATIONAL INSTITUTIONS OF RĒZEKNE MUNICIPALITY. SOCIETY. INTEGRATION. EDUCATION. Proceedings of the International Scientific Conference, 3, 451-462. https://doi.org/10.17770/sie2017vol3.2386