OPTIMIZATION OF THE SIMULATION PROCESS OF PRODUCT SUPPLY FROM THE MANUFACTURER

Abstract

A simulation model of the process of transportation of spare parts from the manufacturer to airports was developed using the method of agent modeling in the AnyLogic environment. During the construction of the model, a GIS map of the OpenStreetMap resource was used, which allows you to add coordinates of objects and build routes as close as possible to real ones. The imitation model was built for the Antonov Serial Plant and seven Ukrainian airports, which need spare parts for aircraft maintenance and repair twice a week. The order comes from the airport to the factory via notification. After that, the truck is loaded, the maximum number of cars for transportation is seven. The time for loading and unloading is two to three hours. After receiving the spare parts, the airport notifies this enterprise by the message «Delivered!». Then the truck is sent back to the enterprise. During the development of the simulation model, the single agent for the factory «Manufacturing», the population of the agent «Airport», which contains a collection of airports with their coordinates, the population of agents «Truck» and the agent type «Order» are created. The process of placing an order for new spare parts is described, given that each airport sends a request of the same form. The logic of order processing by the plant is described, which takes into account: receiving an application, time for loading the truck, sending it to the customer, unloading the truck, notification of delivery and returning the truck to the company. An optimization experiment was created and conducted to minimize the number of cargo vehicles for the supply of spare parts to Ukrainian airports, the loading of which is no more than 85%. The results of the experiment showed that the best allowable value for the use of resources is about 64% when using 2 trucks. According to the results of the conducted research the average value of the resource utilization rate at the enterprise will range from 60-85%.