INFORMATION TECHNOLOGY OF DECISION SUPPORT TO DESIGN THE TRANSPORTATION ORDERS' SERVICING

Abstract

The main purpose of most transport companies is to provide the quality services to customers with minimal costs. At the same time, determination of the number of vehicles and their utilization rate when satisfying transportation orders is the important task, the proper solution of which leads to the full and timely servicing and contributes to an increase of a transport company's competitiveness in the present-day market. Due to the analysis results of the state-of-the-art literature and Internet sources, it has been revealed that the problem of finding the rational fleet size and the rate of its utilization to complete the transportation orders were not fully solved. From the criteria analysis it has been proposed to substantiate the vehicle fleet size according to the car utilization rate to be assigned as the "vehicle working time-to-total working time" ratio. Considering the probabilistic nature of the transportation process, a simulation model to complete the orders by a truck fleet has been developed in the AnyLogic environment. An experimental plan has been developed to reproduce the real transportation order conditions and consisted of 27 series, each of which was of 100 experiments. The variation range of input factors, which was the transportation distance, vehicles' number and orders' hourly intensity were [10;30], [1;3] and [0.6;1], respectively. From the experimental results processing by the regression analysis methods, it has been found that the dependence of changes in the car utilization rate, transportation distance, vehicle' number and orders' intensity was of linear form. The obtained dependence has been estimated via the determination coefficient, which was 0.95, and indicated the high quality of the model proposed. The resulting model allows calculating the required number of vehicles from their operating conditions. In the case study the 2 vehicles were recommended to service the transportation orders. Further research efforts can be taking into account a larger number of influencing factors, increasing their variation range and obtaining dependencies to describe the presented criterion change to acceptable accuracy.