Abstract
In recent years, computational intelligence has been used to solve optimisation problems. An innovative direction in the development of artificial intelligence methods is multiagent methods of intellectual optimisation, which simulate the collective behaviour of insects, animals and other living beings. It indicates the effectiveness of their behaviour, and hence the effectiveness of these methods, and the ability to be involved in solving applied problems. This article is devoted to the study of the development of road transport networks using the metaheuristic ant method of optimisation based on a number of data. The initial data were geospatial layers of information on slope steepness, engineering structures, forests, perennials, land development and hydrographic objects. The parameters of the behaviour of the studied method under different conditions and volumes of input geospatial data are experimentally established. The Max–Min method of multiagent optimisation is modified. The proposed modification takes into account the functional distance – the coefficient of the complexity of the route, which affects its length. This modification had an effective influence on the behaviour of ants and the choice of optimal routes, taking into account the terrain as one of the factors. The result of the advancement is an informational system, which is capable of formulating flexible options for passing optimal alternative routes between specified settlements.