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Application of genetic algorithms for optimisation of agricultural machinery operation in precision farming systems
BUMBÁLEK, Roman
Metaheuristic methods, inspired by physical, biological, chemical, semantic and social phenomena, are used to optimise problems with a large number of possible solutions in a wide range of fields, including agriculture, with a significant part of evolutionary computation, of which genetic algorithms are mainly used for precision agriculture. This paper deals with their implementation in the context of the problem of planning the routes of agricultural machines with the aim of reducing the length of the trajectory of movement both on the headlands and in the inner part of the plot. The developed algorithm consists of several parts, where first the coordinates of the partial routes are calculated and then genetic algorithms are applied to optimise the rotation of the im-plements on the headlands through a suitable combination of their passes with respect to the input parameters, including the turning radius and the tool sweep. The quality of the results obtained is influenced by many factors, such as the size of the population, the number of generations or the type of selection chosen, with better solutions being generated as the number of chromosomes in the population and generations increases, allowing a reduction of more than 37 % in the distance travelled when turning on he-adlands, which can directly translate into savings in working time, fuel and reduced soil compaction.
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