Modeling of Goods Movement by a Group of Unpiloted Aerial Vehicles Based on the Ant Colony Algorithm

This article is about issues that happen during moving a large number of similar goods are located on certain site and concentrating them in one place (warehouse). These include imperfect conditions facilities, unsatisfactory state transport service, exhausted rolling stocks, low quality or overloading routs, remote sites goods’ reception delivery points, poor managing moving, unexpected outcomes, etc. In order to solve these problems the authors recommend using group unpiloted air vehicles (UAV) solving related an efficient their by means stochastic optimization algorithm, namely ANTS ant algorithm. Authors propose improved methods algorithm ANT uses function changing intensity digital phenomenon, and, unlike existing algorithms, not linear, but cubic dynamic scaling change phenomenon allow us focus searching only short routes shipping also consideration new one. The experiments movement different quantities involved UAV have been conducted modeling WeBots test Mavic 2Pro UAVs for 150 g typical loads (storehouse). assessment efficiency was base its results relation between quantity shipped time defined. It found efficacy this process increases with increase because decreases. Also, it every next causes smaller due waiting line load’s disembarking.