Strategic planning of cargo flows based on the product distribution model

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Lebedeva O.A., Gozbenko V.E. Strategicheskoye planirovaniye gruzopotokov na osnove modeli raspredeleniya produktov [Strategic planning of cargo flows based on the product distribution model]. Sovremennye tekhnologii. Sistemnyi analiz. Modelirovanie [Modern Technologies. System Analysis. Modeling], 2020, No. 4 (68), pp. 183–189. – DOI: 10.26731/1813-9108.2020.4(68).183-189

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The article identifies the problem of the distribution of cargo flows in a multimodal network, taking into account the aspects of the transport system in the selected network representation. Network models allow predicting flows by modeling a physical network at the level of detail of a country or large region. Demand for transportation services is exogenous and can be obtained by calculation, observation method or other sources. The prospects of integration with econometric models of demand are considered. The emphasis is on network representation, taking into account overload in a static model intended for use in comparative studies or for multi-period analysis with discrete time. The multi-product model is formulated in a general way, allowing you to include both convex and asymmetric cost functions. Nevertheless, some assumptions made regarding the structure of cost functions simplify and allow solving large problems in a reasonable time. The solution algorithm is reduced to the following procedures: a network view is selected to integrate transportation and transshipment options; then a multi-purpose model is formulated and the functions of average and marginal cost are analyzed. Next, the shortest paths with transportation costs in the selected network are calculated; effectiveness is demonstrated and model testing is evaluated. Strategic freight traffic planning model, suitable for international and regional freight transportation systems. New aspects of the model are a way of representing the network, specification of requirements, an algorithm for solving mathematical programming, adaptation of the shortest path algorithm, and the use of numerical analysis.

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