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An integrated approach is proposed in the study of rational schemes for the distribution of cargo flows at a regional transport loop for multimodal transportation, considered within the framework of an oligopolistic market. A technique has been developed for the parallel application of two approaches, differing in their mathematical nature, to the issues of increasing the economic efficiency of these transportations. The results obtained by the previously developed method of economic and geographical delimitation of «influence areas» of loading stations serve as a justification for the correctness of the results obtained by using an algorithm based on the Pareto optimization of the freight transportation process. Rational variants for organizing the freight transportation, taking into account time and cost indicators, have been obtained. The system of analytical calculations is used as a software tool to obtain a mathematically sound and transport–logistic diversified model of a regional oligopolistic freight market.
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153--165
Opis fizyczny
Bibliogr. 15 poz.
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autor
- Rostov State Transport University (RSTU). Rostovskogo Strelkovogo Polka Narodnogo Opolcheniya Sq. 2, 344038, Rostov-On-Don, Russia
autor
- Rostov State Transport University (RSTU). Rostovskogo Strelkovogo Polka Narodnogo Opolcheniya Sq. 2, 344038, Rostov-On-Don, Russia
autor
- Rostov State Transport University (RSTU). Rostovskogo Strelkovogo Polka Narodnogo Opolcheniya Sq. 2, 344038, Rostov-On-Don, Russia
autor
- Rostov State Transport University (RSTU). Rostovskogo Strelkovogo Polka Narodnogo Opolcheniya Sq. 2, 344038, Rostov-On-Don, Russia
autor
- Rostov State Transport University (RSTU). Rostovskogo Strelkovogo Polka Narodnogo Opolcheniya Sq. 2, 344038, Rostov-On-Don, Russia
autor
- Rostov State University of Economics Bolshaya Sadovaya 69, 344002, Rostov-on-Don, Russia
Bibliografia
- 1. Gao, Y. & Yang, L. & Li, S. Uncertain models on railway transportation planning problem. Applied Mathematical Modelling. 2016. Vol. 40. Nos. 7-8. P. 4921-4934. 1 t 2 t c Mathematical modeling of cargo flow distribution… 165
- 2. Maiyar, L.M. & Thakkar, J.J. A combined tactical and operational deterministic food grain transportation model: Particle swarm based optimization approach. Computers & Industrial Engineering. 2017. Vol. 110. P. 30-42.
- 3. Mogale, D.G. & Cheikhrouhou, N. & Tiwari, M.K. Modelling of sustainable food grain supply chain distribution system: a bi-objective approach. International Journal of Production Research. 2020. Vol. 58. No. 18. P. 5521-5544.
- 4. Maiyar, L.M. & Thakkar, J.J. Robust optimisation of sustainable food grain transportation with uncertain supply and intentional disruptions. International Journal of Production Research. 2020. Vol. 58. No. 18. P. 5651-5675.
- 5. Tian, W & Cao, C. A generalized interval fuzzy mixed integer programming model for a multimodal transportation problem under uncertainty. Engineering Optimization. 2017. Vol. 49. No. 3. P. 481-498.
- 6. Sun, Y. & Liang, X. & Li, X. & Zhang, C. A Fuzzy Programming Method for Modeling Demand Uncertainty in the Capacitated Road–Rail Multimodal Routing Problem with Time Windows. Journals Symmetry. 2019. Vol. 11. No. 1. P. 91. Available at: https://doi.org/10.3390/sym11010091.
- 7. Aulin, V. & Lyashuk, O. & Pavlenko, O. & Velykodnyi, D. & Hrynkiv, A. & Lysenko, S. & Holub, D. & Vovk, Y. & Dzyura, V. & Sokol, M. Realization of the Logistic Approach in the International Cargo Delivery System. Communications - Scientific letters of the University of Zilina. 2020. Vol. 21. No. 2. P. 3-12.
- 8. Kwon, S. & Park, K. & Lee, C. & Kim, S.S. & Kim, H.J. & Liang, Z. Supply Chain Network Design and Transshipment Hub Location for Third Party Logistics Providers. Computational Science and Its Applications – ICCSA 2006. Lecture Notes in Computer Science. 2006. Vol 3982. P. 928-933.
- 9. Prachi, A. & Talari, G. Multi-choice stochastic transportation problem involving logistic distribution. Advances and Applications in Mathematical Sciences. 2018. Vol. 18. No. 1. P. 45-58.
- 10. Wiradanti, B. & Pettit, S. & Potter, A. & Abouarghoub, W. Ports, peripherality and concentration – deconcentration factors: a review. Maritime Business Review. 2018. Vol. 3. No. 4. DOI: 10.1108/MABR-09-2018-0040.
- 11. Nežerenko, O. & Koppel, O. & Tuisk, T. Cluster approach in organization of transportation in the Baltic Sea Region. Transport. 2015. Vol. 32. No. 2. P. 1-13.
- 12. Valls, J. & Langen, P. & Garcia-Alonso, L. & Vallejo-Pinto, J. Understanding Port Choice Determinants and Port Hinterlands: Findings from an Empirical Analysis of Spain. Maritime Economics & Logistics. 2020. Vol. 22. P. 53-67.
- 13. Chislov, O.N. & Zadorozhniy, V.M. & Lomash, D.A. & Chebotareva, E.A. & Solop, I.A. & Bogachev, T.V. Methodological Bases of Modeling and Optimization of Transport Processes in the Interaction of Railways and Maritime Transport. Modern Traffic Engineering in the System Approach to the Development of Traffic Networks. 2020. Vol 1083. P. 79-89.
- 14. Chislov, O.N. & Zadorozhniy, V.M. & Bogachev, T.V. & Kravets, A.S. & Egorova, I.N. & Bogachev, V.A. Time Parameters Optimization of the Export Grain Traffic in the Port Railway Transport Technology System. Smart and Green Solutions for Transport Systems. 2020. Vol. 1091. P. 126-137.
- 15. Moulin, H. Axioms of Cooperative Decision Making (Econometric Society Monographs). Cambridge: Cambridge University Press, New York. 1989. 348 p.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-35570592-517f-4628-b193-eced1c0b2432
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