Vitalii Svatko

Bio: Vitalii Svatko is an academic researcher. The author has contributed to research in topics: Traffic flow & Ant colony optimization algorithms. The author has co-authored 1 publications.

Simulation of Processes for Optimizing the Delivery Routes of Goods on Urban Road Networks by a Synergetic Approach

Abstract: A synergetic approach for simulation the processes of optimizing cargo delivery routes, taking into account the non-stationary dynamics of traffic flows on sections of the urban road network is proposed. Here, route optimization is carried out using a modified ant colony self-organization algorithm. At that, the analytical dependences of the change in the speed of the traffic flow on the characteristic time and load density on sections of the road network are determined in the framework of the synergetic Lorentz model. Simulation of the building of optimal routes is carried out using the proposed approach on the example of the Kiev city. The possibility of using this approach to solve the problems of efficient control of the process of routing freight traffic in conditions of the real dynamics of traffic flows is shown. Prospects for the use of the developed approach in intelligent transportation systems are discussed, for example, in solving problems of dynamic routing of vehicles using traffic prediction information.

The optimization of cargo delivery processes with dynamic route updates in smart logistics

Abstract: The object of research is the processes of transport logistics management under the influence of non-stationary factors of different nature on the functioning of street-road networks (SRN) in cities. The task of dynamic routing at large and variable loading of SRN sections is solved by managing the processes of cargo delivery in real time within the framework of the implementation of the Smart Logistics concept. Simulation studies of cargo delivery routing with dynamic real-time route updating using a modified ant colony algorithm and data on the dynamics of traffic flow (TF) were conducted using an SRN in the city of Kyiv as an example. Here, experimental data were obtained using motion sensors of intelligent transport systems. During the optimization, current data were used acquired online within the framework of the Internet of Things technology, as well as historical data obtained over past periods of time and averaged using Big Data (BD) technology. Route optimization at each stage of real-time updates was achieved using a modified ant colony algorithm. This method has a sufficiently high optimization performance and makes it possible, unlike many other intelligent methods, to directly take into account the non-stationary dynamics of TF within SRN. It is shown that the use of properly averaged BD historical data allows for more efficient planning of transport routes. The simulation studies indicate the possibility of using the proposed approach by transport companies and authorities to solve the problems of managing logistics flows in an automated mode under conditions of complex, unpredictable traffic

Dynamic routing of cargo delivery processes in cities base on synergetic approach

Abstract: The paper proposes synergetic approach for simulation the processes of optimization of routes for the delivery of goods taking into account the non-stationary dynamics of traffic flows on sections of the urban road network. Within the framework of synergetic Lorentz model, the analytical dependences of the change in the speed of the traffic flow on the characteristic time of the change in the dynamics of the traffic flow and the density of the traffic flow in the network sections are determined. Further, based on the obtained dependence of the traffic flow speed on its density by using a modified self-organization algorithm of the ant colony, the route on the network is optimized. Here the urban road network is represented as a bidirectional weighted graph. The main element of the modification is that it implements the possibility of asynchronous movement of the each ant colony agent at a certain speed. In addition, it is also possible to fix the results of optimization of a partially traveled path for calculating a further route when the edge weight (length) of the graph changes during the movement. This allows you to management the route optimization process, taking into account the dynamic state of the network, which depends on the speed of movement of vehicles on certain sections of the 171 network. These changes in speed can be caused by an increase in the congestion of network sections, the occurrence of traffic jams, emergency situations, etc. To test the proposed method, simulation of route optimization processes was carried out within the framework of the traveling salesman problem, taking into account the real dynamics of traffic flows on the example of the road network of Kyiv city. Here, when conducting research on some selected sections of the network, the average density of traffic flows at certain points in time during the day was experimentally determined. Based on the simulation results, a number of effects were identified. These effects are associated with the rebuilding of optimal routes when the average speeds of vehicles on the model sections of the network decrease to certain boundary values corresponding to certain modes of traffic flow. The paper discusses the possibility of using the proposed method in intelligent transportation systems. In particular, this method can be used to solve dynamic vehicle routing problems using information about traffic prediction. KEYWORDS: TRAFFIC FLOW, URBAN ROAD NETWORK, SYNERGETIC LORENTZ MODEL, SYNERGETIC APPROACH, ANT ALGORITHM