Modeling of Goods Movement by a Group of Unpiloted Aerial Vehicles Based on the Ant Colony Algorithm
DOI:
https://doi.org/10.31649/1997-9266-2022-164-5-73-79Keywords:
unmanned aerial vehicles, number of moved loads, digital pheromone, ant algorithm, moving loadsAbstract
This article is about issues that happen during moving a large number of similar goods that are located on a certain site and concentrating them in one place (warehouse). These issues include imperfect conditions of facilities, unsatisfactory state of transport service, exhausted rolling stocks, low quality or overloading of transport routs, remote sites of goods’ reception and delivery points, poor managing of goods moving, unexpected outcomes, etc. In order to solve these problems the authors recommend using of a group of unpiloted air vehicles (UAV) and solving the issues related to an efficient managing of their moving by the means of stochastic optimization algorithm, namely the ANTS ant algorithm. Authors propose the improved methods of an ant algorithm ANT that uses the function of changing the intensity of the digital phenomenon, and, unlike existing algorithms, uses not linear, but cubic dynamic scaling of the change of the digital phenomenon that allow us to focus on searching not only the short routes of shipping but also on consideration of a new one. The experiments on goods movement by the different quantities of involved UAV have been conducted using the modeling in WeBots and the test Mavic 2Pro UAVs for shipping 150 g typical loads to the one site (storehouse). The assessment of efficiency of loads shipping was conducted on the base of its results and a relation between a quantity of shipped loads and a time of shipping was defined. It was found that the efficacy of this process increases with increase in the number of UAV because the time of moving decreases. Also, it was found that the every next increase in the number of involved UAVs causes the smaller increase in efficiency due to the waiting in a line for a load’s disembarking.
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