Abstract
This article considers the use of the entropy method in the optimization and forecasting of multimodal transport under conditions of risks that can be determined simultaneously by deterministic, stochastic and fuzzy quantities. This will allow to change the route of transportation in real time in an optimal way with an unacceptable increase in the risk at one of its next stages and predict the redistribution of the load of transport nodes. The aim of this study is to develop a mathematical model for the optimal choice of an alternative route, the best for one or more objective functions in real time. In addition, it is proposed to use this mathematical model to estimate the dynamic change in turnover through intermediate transport nodes, forecasting their loading over time under different conditions that also include long-term risks which are significant in magnitude. To substantiate the feasibility of the proposed mathematical model, the analysis and forecast of cargo turnover through the seaports of Ukraine are presented, taking into account and analysing the existing risks.
Highlights
Multimodal cargo transportation involves the existence of a chain of successive transportations using different modes of transport
For an example of practical use of the proposed mathematical model, we do not give its application in real time for the transportation of commercial goods, as it is associated with both trade secrets and is a narrow utilitarian application, which is uninteresting to the general public, but analyze and forecast redistribution of load for a longer time interval for transport hubs—seaports of Ukraine as transit points of multimodal transportations
This paper proposes a mathematical model of the optimal choice of alternative routes or stages of multimodal transportation routes in case of increased risk on existing routes or subsequent stages of transportation on the condition of certain threshold values
Summary
Multimodal cargo transportation involves the existence of a chain of successive transportations using different modes of transport. During transportation, it may turn out that at one of the stages of the route, the circumstances of transportation have become less favorable or extremely unfavorable, which is much worse, unacceptably increasing the risk of transportation. These risks are determined by many parameters that can be measured on different scales. The article [2] proposes double multi-objective linear programming to simplify the calculation of optimization problems by their linearization It should be borne in mind that the approach [2] is proposed to avoid the use of classical optimization methods. This was taken into account when developing the mathematical approach proposed by the authors
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