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Tytuł artykułu

Improving the methodology for optimizing multimodal transportation delivery routes and cyclic schedules in a transnational direction

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This study considers the task of planning the routes of multimodal transnational cargo transportation. Due to the extremely long length of such routes, delivery times and costs per cargo unit are extremely important. Delays in various types of transport and in the case of cargo transshipment are associated not only with the growth of cargo flows but also with the inconsistency of vehicle schedules. The purpose of this study is to improve the previously developed methodology for optimizing multimodal cargo transportation, taking into account the need for its application to transnational transport corridors. The content of the formulated network problem is reduced to a modification of the traveling salesman problem with an unknown number of transport points the route should pass through. Such a problem is NP-hard due to the time complexity of the algorithms. A modified algorithm has been developed, according to which the general problem with the number of N points is divided into several subproblems. Transport points are grouped into consecutive subsets that are related by only one non-alternative way of transportation. This way can be any “bottleneck” of the transport network or an artificially created one. Such a decomposition of the problem gives a set of partial solutions, which were combined into the final optimal solution. The obtained solution to the routing problem of multimodal routes takes into account the cyclical schedules of the transport operation and gives a guaranteed exact optimum for calculations performed within the permissible time. In addition to determining the optimal route, the algorithm makes it possible to determine the required number of vehicles and their work schedules depending on the total cargo flow on the route.
Czasopismo
Rocznik
Strony
157--170
Opis fizyczny
Bibliogr. 20 poz.
Twórcy
autor
  • Rzeszow University of Technology, Department of Roads and Bridges, Powstańców Warszawy Ave. 12, Rzeszów, 35-959, Poland
  • Academy of Logistics and Transport, 97 Shevchenko str., Almaty, 050022, Kazakhstan
  • National Transport University, 1 M. Omelianovycha-Pavlenka str., Kyiv, 01010, Ukraine
  • M. Dulatova University of Engineering and Economics, 59 Chernyshevskogo str., Kostanay, 110000, Kazakhstan
  • International Transport and Humanitarian University, 32A micr. Zhetysu-1, Almaty, 050063, Kazakhstan
  • L’viv National University of Nature Management, Department of Agricultural Engineering and Technical Service, 1 V. Velykogo str., L’viv Region, Dubliany, 79020, Ukraine
Bibliografia
  • 1. Li, X. & Xie, C. & Bao, Z. A multimodal multicommodity network equilibrium model with service capacity and bottleneck congestion for China-Europe containerized freight flows. Transportation Research Part E: Logistics and Transportation Review. 2022. Vol. 164. No. 102786.
  • 2. European Statistical System (ESS). Available at: https://www.efta.int/statistics/european-statistical- system.
  • 3. Kang, F. & Li, X. & Li, J. Analysis of Multi-objective Multimodal Transport Route Planning Based on Genetic Algorithm. In: Application of Intelligent Systems in Multi-modal Information Analytics: 2021 International Conference on Multi-modal Information Analytics (MM1A 2021). Vol. 1. Springer International Publishing. 2021. P. 30-38.
  • 4. Song, W. Research on optimization of multimodal transport path under low-carbon background. In: International Conference on Algorithms, Microchips and Network Applications. SPIE. 2022. P. 626-630.
  • 5. Oliskevych, M. & Taran, I. & Volkova, T. & Klymenko, I. Simulation of cargo delivery by road carrier: case study of the transportation company. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2022. Vol. 2. P. 118-123.
  • 6. Yao, Yu. et al. ADMM-based problem decomposition scheme for vehicle routing problem with time windows. Transportation Research Part B: Methodological. 2019. Vol. 129. P. 156-174.
  • 7. Neves-Moreira, F. et al. Solving a large multi-product production-routing problem with delivery time windows. Omega. 2019. Vol. 86. P. 154-172.
  • 8. Teo, H.C. & Lechner, A.M. & Walton, G.W. & Chan, F.K.S. & Cheshmehzangi, A. & Tan-Mullins, M. & Chan, H.K. & Sternberg, T. & Campos-Arceiz, A. Environmental impacts of infrastructure development under the Belt and Road Initiative. Environments. 2019. Vol. 6(6). No. 72.
  • 9. Prokudin, G. & Oliskevych, M. & Сhupaylenko, O. & Maidanik, K. Optimization model of freight transportation on the routes of international transport corridors. Journal of Sustainable Development of Transport and Logistics. 2020. Vol. 5(1). P. 66-76.
  • 10. Boyko, N. & Muzyka, M. Analysis of Multimodal Data for Classification Problems by Using Methods of Machine Learning. In: 2021 IEEE 8th International Conference on Problems of Infocommunications, Science and Technology (PIC S&T). 2021. P. 525-534.
  • 11. Bazaluk, O. & Kotenko, S. & Nitsenko, V. Entropy as an objective function of optimization multimodal transportations. Entropy. 2021. Vol. 23(8). No. 946.
  • 12. Pavlenko, O. & Muzylyov, D. & Shramenko, N. & Cagânovâ, D. & Ivanov, V. Mathematical Modeling as a Tool for Selecting a Rational Logistical Route in Multimodal Transport Systems. EAI/Springer Innovations in Communication and Computing. 2023. P. 22-37.
  • 13. Hao, C. & Yue, Y. Optimization on combination of transport routes and modes on dynamic programming for a container multimodal transport system. Procedia Engineering. 2016. Vol. 137. P. 382-390.
  • 14. Mazaraki, A. & Matsiuk, V. & Ilchenko, N. & Kavun-Moshkovska, O. & Grygorenko, T. Development of a multimodal (railroad-water) chain of grain supply by the agent-based simulation method. Eastern-European Journal of Enterprise Technologies. 2020. Vol. 6(3-108). P. 14-22.
  • 15. Garcia, J. & et al. Solving multi-modal and uni-modal transportation problems through TIMIPlan. IFAC Proceedings Volumes. 2012. Vol.45(24). P. 203-208.
  • 16. Taran, I. & Olzhabayeva, R. & Oliskevych, M. & Danchuk, V. Structural optimization of multimodal routes for cargo delivery. Archives of Transport. 2023. Vol. 67(3). P. 49-70.
  • 17. A Survey on Travelling Salesman Problem. Available at: https://micsymposium.org/mics_2010_proceedings/mics2010_submission_51.pdf.
  • 18. Kyi, M.T. & Naing, L.L. Application of Ford-Fulkerson algorithm to maximum flow in water distribution pipeline network. International Journal of Scientific and Research Publications. 2018. Vol. 8(12). P. 306-310.
  • 19. Akyüz, M.H. & Dekker, R. & Azadeh, S.S. Partial and complete replanning of an intermodal logistic system under disruptions. Transportation Research Part E: Logistics and Transportation Review. 2023. Vol. 169. P. 102968.
  • 20. SEARATES by DP World. Available at: https://www.searates.com/ua/services/distances-time/.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-ee878300-f528-4a49-8f6d-0c71473f3ebb
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