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Optimization of travel routes based on modified genetic and ant algorithms

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Języki publikacji
EN
Abstrakty
EN
In the article, propose to use modified mating operators and initialization genetic and ant algorithms to solve transport problems in tourism. The article analyzes modern methods of optimization of routes used to transport tourists between the settlements of view of efficient use of resources. By analyzing the behavior of ant colonies, such as finding the shortest route by providing mating pheromones and features two solutions genetic algorithm developed algorithms for finding the optimal route, costing resources search distance, time, route, storing executed routes. The paper present description created system for mobile phones operating system IOS, which performs all operations listed above.
Twórcy
autor
  • Lviv Polytechnic National University
Bibliografia
  • 1. Kazharov A. 2010. Ant algorithms to solve transport problems // Russian Academy of Sciences. Theory and management systems, рр. 32–45
  • 2. Yemelyanova S. 2008 Solving transportation problems with a cluster clients using genetic algorithms // Fuzzy Systems and Computing, рр. 195–199.
  • 3. Gladkov L. 2006. Genetic algorithms: Tutorial // Physics and mathematics, 320 р.
  • 4. Goryachev Y. 2001. Genetic algorithms optimize multi conflict, 102 p.
  • 5. Kureychyk V. 2012. Application of genetic algorithm for solving the problem of three-dimensional packaging // PFC. Engineering, рр. 8–14.
  • 6. Bova V. 2010. The integrated subsystem hybrid and combined search and management problems of designing // PFC. Engineering, рр. 37–42.
  • 7. Yermeyev A. 2000. Development and analysis of genetic and hybrid algorithm for solving discrete optimization, p. 22.
  • 8. Kureychyk, V. 2006 Search adaptation: Theory and Practice / M.: Physics and mathematics, 272 p.
  • 9. V. Pasichnyk, V. Savchuk 2015. Mobile Information Technologies for Tourism Domain. ECONTECHMOD: an international quarterly journal on economics of technology and modelling processes, Vol. 4, No. 2, рр. 25–32, 2015.
  • 10. Lytvyn V., Medykovskyj M., Shakhovska N., Dosyn D. (2012). “Intelligent Agent on the Basis of Adaptive Ontologies,”. Journal of Applied Computer Science, Vol. 20, No. 2, рр. 71–77.
  • 11. Shakhovska N., Veres O., Hirnyak M. 2016. Generalized formal model of Big Data. ECONTECHMOD: an international quarterly journal on economics of technology and modelling processes, Vol. 5, No. 2, рр. 33–38, 2016 (in Polish).
  • 12. Pasichnyk V., Lozytskyy O., Savchuk V. 2016. Personified information technology to support the tourist with excursion content in DAISY format ECONTECHMOD: an international quarterly journal on economics of technology and modelling processes. Vol. 5, No. 2, рр. 77–86, 2016.
  • 13. Jannach D., Recommender Systems: An Introduction / D. Jannach, M. Zanker, A. Felfernig, G. Friedrich – Cambridge University Press, New York, 2010,– 352 p.
  • 14. Kask S., Modeling tourist and community decision making. The SAVE Market / S. Kask, C. Kline, K. Lamoureux, Annals of Tourism Research, 2011, Vol. 38, No. 4, рр. 1387–1409.
  • 15. Artemenko O., Dynamic characteristics of perspective touristic information technologies / Olga Artemenko, Natalya Kunanec, Volodymyr Pasichnyk, Valeriya Savchuk // Econtechmod an international quarterly journal, 2015, No. 4, Vol. 4, рр. 107–118.
  • 16. Bin R., Research on Tourism Service Intelligent Recommendation System Based on Apriori-MD Algorithm / Rao Bin // Applied Mechanics and Materials, 2014, Vol. 651–653, рр. 1642–1646. © (2014) Trans Tech Publications, Switzerland doi: 10.4028/www.scientific.net/AMM.651-653. 1642 p.
  • 17. Borrаs J., Intelligent tourism recommender systems: A survey / J. Borrаs, A. Moreno, A. Valls // Expert Systems with Applications, 2014, Vol. 41, рр. 7370–7389.
  • 18. Fedushko S., Syerov Yu., and Korzh R., “Validation of the user accounts personal data of online academic community” IEEE XIIIth Intern. Conf. “Modern Problems of Radio Engineering, Telecommunications and Computer Science”, Lviv- Slavske, February 23–26, 2016, рр. 863–866.
  • 19. Fedushko S. “Development of verification system of socio-demographic data of virtual community member” Radio Electronics Computer Science Control, Article No. 3, pp. 87–92, 2016.
  • 20. Dosyn D., Lytvyn V., Yatsenko A. (2012) DPoptimization of steel corrosion protection techniques in the intelligent diagnostic system // Physicochemical Mechanics of Materials, No. 9. – Lviv, 2012, рр. 329–333.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
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Bibliografia
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