Development of a multimodal (railroad-water) chain of grain supply by the agent-based simulation method
Keywords:multimodal logistics, grain supply chain, agent-based simulation, railroad and water route
The results of the simulation of a multi-element chain of grain supply by the rail and water multimodal route were shown. Mathematical substantiation of the optimization problem was presented. The minimum cargo delivery time was selected as the optimization criterion. The limits for the admissible use (loading) of fleets of transport units of railroad and water transport were selected as optimization constraints. The optimization model is a multi-parametric problem of stochastic programming. The objective function of the model was represented in implicit expression. The search for the solution of the optimization model was performed using experiments with the developed simulation model.
The simulation model is based on the discrete-event and agent-based principles, it simulates the interaction of two railroad and one sea transport and technological lines, as well as terminal points of accumulation, storage, and reloading of cargo batches. One ton of wheat grain acts as a part of the cargo module.
The simulation model was developed in AnyLogic RE (USA) and Java SE (USA) environments. The algorithm of the simulation model involves the interaction of populations of agents of transport junction points; agents of transport and technological lines; populations of agents of fleets of transport units; agents of information orders for transportation. The model was implemented using the example of the actual process of grain supply from Ukraine to Egypt.The model was studied using the integer optimization method. As a result of experiments, the optimal values of the required stock of cars, locomotives, and naval vessels were established. In addition, the required capacity of granaries at the shipping stations and seaports’ terminals, as well as the necessary capacity of track development of railroad stations, were found. The established average delivery time was within 185 hours
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Copyright (c) 2020 Anatolii Mazaraki, Viacheslav Matsiuk, Nataliia Ilchenko, Olha Kavun-Moshkovska, Tetyana Grygorenko
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