INFORMAZIONI SU QUESTO ARTICOLO

Cita

1. Ali, H., Haris, M., Hadi, F., Ahmadullah, Salman and Shah, Y (2016) Solving Traveling Salesman Problem through Optimization Techniques Using Genetic Algorithm and Ant Colony Optimization. Journal of Applied Environmental and Biological Sciences, 6(4S), 55-62.Search in Google Scholar

2. Balasescu, S. and Balasescu, M. (2014) Optimization methods for supply chain activities. Bulletin of the Transilvania University of Brasov Series V: Economic Sciences, 7(56), 9-16.Search in Google Scholar

3. Bullnheimer, B., Hartl, R. and Straub, Ch. (1997) A new rank based version of the Ant System. A computational study. Adaptive Information Systems and Modelling in Economics and Management Science, 1, 1-14.Search in Google Scholar

4. Chandekar, N. and Jayachandran Pillai, M. (2017) A Comparative Study of GA and ACO for Solving Travelling Salesman Problem. International Journal of Mechanical and Production Engineering, 5(11), 34-37.Search in Google Scholar

5. Danchuk, M.V. and Kravchuk, A.P. (2013) Features of Value-at-risk Methodology Application for Business Risks Estimation under Nonlinear Dynamics of Economic Development. Actual Problems of Economic, 148, 207-213.Search in Google Scholar

6. Danchuk, V. and Svatko, V. (2012) Modified ant method of optimizing the route in the dynamic travelling salesman problem. Visnik National Transport University, 25, 378-382.Search in Google Scholar

7. Danchuk, V., Bakulich, O. and Svatko, V. (2017) An Improvement in Ant Algorithm Method for Optimizing a Transport Route with Regard to Traffic Flow. Procedia Engineering, 187, 425-434.10.1016/j.proeng.2017.04.396Search in Google Scholar

8. Dorigo, M. and Gambardella, L. M. (1997) Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem. IEEE Transactions on Evolutionary Computation, 1, 53-66.10.1109/4235.585892Search in Google Scholar

9. Dorigo, M. and Gambardella, L.M. (1997) Ant colonies for the traveling salesman problem. BioSystems, 43 (2), 73–81.10.1016/S0303-2647(97)01708-5Search in Google Scholar

10. Dorigo, M., Maniezzo, V. and Colorni, A. (1996) The Ant System: Optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man, and Cybernetics-Part B, 26(1), 29-41.10.1109/3477.48443618263004Search in Google Scholar

11. Gambardella, L.M. and Dorigo, M. (1995) Ant-Q: A Reinforcement Learning Approach to the Traveling Salesman Problem. In: Proceedings of the Twelfth International Conference on Machine Learning, Tahoe City, California, July 9–12, 1995, 252-260.Search in Google Scholar

12. Glover, F., Kochenberger, G. (2003) Handbook of Metaheuristics, Series: International Series in Operations Research & Management Science, 57, 570 p.10.1007/b101874Search in Google Scholar

13. Goldberg, A., Kaplan, H., and Werneck, R. (2005) Reach for A*: Efficient Point-to-Point Shortest Path Algorithms, Technical Report MSR-TR-2005-132, Microsoft Research.10.1137/1.9781611972863.13Search in Google Scholar

14. Haken, H. (2004) Synergetics. Introduction and Advanced Topics. Berlin, Heidelberg: Springer, 758p.10.1007/978-3-662-10184-1_2Search in Google Scholar

15. Karmakar, R. (2016) Solving TSP Using Improved Elitist Ant System Based on Improved Pheromone Strategy and Dynamic Candidate List. MAYFEB Journal of Computer Science, 1, 8-15.Search in Google Scholar

16. Kerner, B.S. (2004) The Physics of Traffic. Berlin, Heidelberg, New York: Springer, 683 p.Search in Google Scholar

17. Knight, H. (2014) New algorithm can dramatically streamline solutions to the ‘max flow’ problem. MIT News, 2014, 21–26.Search in Google Scholar

18. Lobanov, E., Silianov, V., Sitnikov, L. and Sapegin, L. (1970) Throughput capacity of highways. M.: Transport, 152.Search in Google Scholar

19. Lukinskiy, V. and Dobromirov, V. (2016) Methods of evaluating transportation and logistics operations in supply chains. Transport and Telecommunication, 17, 55-59.10.1515/ttj-2016-0006Search in Google Scholar

20. McCall, J. (2005) Genetic algorithms for modelling and optimization. Journal of Computational and Applied Mathematics, 184, 205-222.10.1016/j.cam.2004.07.034Search in Google Scholar

21. Potvin, J.-Y. (1996) Genetic algorithms for the traveling salesman problem. Annals of Operations Research, 63, 339-370.10.1007/BF02125403Search in Google Scholar

22. Prokudin, G., Chupaylenko, O., Dudnik, O., Dudnik, A., and Omarov, D. (2016) Improvement of the Methods for Determining Optimal Characteristics of Transportation Networks. Eastern-European Journal of Enterprise Technologies, 6/3(84), 54-61. - https://doi.org/10.15587/1729-4061.2016.8521110.15587/1729-4061.2016.85211Search in Google Scholar

23. Puchkovska, G.O., Makarenko, S.P., Danchuk, V.D. and Kravchuk, A.P. (2005) Temperature Study of Resonance Intermolecular Interaction in Normal Long-Chain Carboxylic Acid Crystals Using IR Absorption Spectra. Journal of Molecular Structure, 744-747, 53-58.10.1016/j.molstruc.2005.01.002Search in Google Scholar

24. Qingyou, Y. and Zhang, Q. (2015) The Optimization of Transportation Costs in Logistics Enterprises with Time-Window Constraints. Discrete Dynamics in Nature and Society, 2015, 10-15.Search in Google Scholar

25. Rejer, I. and Lorenz, K. (2015) Classic genetic algorithm vs. genetic algorithm with aggressive mutation for feature selection for a brain-computer interface. Przegląd Elektrotechniczny, 91(2), 98-102.Search in Google Scholar

26. Resolution of the Cabinet of Ministers of Ukraine from 10.11.2017 № 883 «On changes to the rules of the road». Available at: http://zakon3.rada.gov.ua/laws/show/883-2017-%D0%BFSearch in Google Scholar

27. Routing service Google map. Available at: https://www.google.com.ua/maps/Search in Google Scholar

28. Statistics price of cargo in Ukraine. Available at:http://degruz.com/price_statisticsSearch in Google Scholar

29. Stützle, T. and Hoos, H. (1997) MAX-MIN Ant System and local search for the traveling salesman problem. IEEE International Conference on Evolutionary Computation, 309-314.10.1109/ICEC.1997.592327Search in Google Scholar

30. Video surveillance resource for road network in Kiev. Available at:http://videoprobki.uaSearch in Google Scholar

31. Xiaojun, L., Zhonghua, N. and Xiaoli, Q. (2016) Application of Ant Colony Optimization Algorithm in Integrated Process Planning and Scheduling. The International Journal of Advanced Manufacturing Technology, 84 (1), 393–404.Search in Google Scholar

32. Zhaoyuan, W., Huanlai, X. and Tianrui, L. (2016) A Modified Ant Colony Optimization Algorithm for Network Coding Resource Minimization. IEEE Transactions on Evolutionary Computation, 20 (3), 325-342.Search in Google Scholar

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