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The paper discusses solving the problem of machine mobility using an hybrid evolutionary modeled algorithm. Until now, the problem of optimizing the mobility of machines has been considered as a private problem that does not take into account the completeness of all factors affecting the process. The goal of our research is to develop a method that allows it to be used effectively to find optimization problems. The proposed method includes three concepts: optimization of mode, structural parameters and control process. We relied on the basic provisions of mathematical statistics, methods of mathematical modeling, evolutionary modeling and parameter optimization. A system of functions has been compiled to perform the task of multi-criterion optimization of the mobility parameters of forest equipment based on four criteria: cross-country ability, speed, relative turning radius and probability of failure-free operation. A metagenetic approach has been applied, which made it possible to achieve the best combination of traditionally used optimization methods and a genetic algorithm. Tests of the received algorithm were performed on standard tasks. The test results showed that the proposed method makes it possible to obtain high-quality solutions at minimum cost. The PRADIS//FRONT information system was used in calculations and plotting.

Ways to solve the optimal mobility of forest complex machines in the formation of a logging enterprise