Akademik Veri Yönetim Sistemi
4th International Informatics and Software Engineering Conference, IISEC 2023, Ankara, Türkiye, 21 - 22 Aralık 2023, (Tam Metin Bildiri)
Depot management in the military field is of critical importance for the safe storage, protection, and management of military supplies, equipment, and guns, especially during wartime and military operations. For military depot management, factors such as security, location of depots, stock management and updating, and logistics must be managed correctly. Heuristic algorithms such as genetic algorithms are used in complex problems that include depot location finding, stock management, logistics management, and vehicle routing problems.Heuristic algorithms try to produce optimum solutions by addressing the problems of reducing distance, time, and the number of vehicles in vehicle routing problems (VRP). For this reason, optimization algorithms are used in such problems (VRP). One of the most frequently used algorithm types among the heuristic algorithms used to solve optimization problems is genetic algorithms. The genetic algorithm includes the parameters in the problem in the gene structure and searches for the best solution by performing crossover and mutation operations among themselves.In this study, a vehicle routing problem for the supply of materials needed by soldiers during a military operation was defined and the routing solution was realized with the genetic algorithm method. Google Maps API was used for mapping and determining the soldier's location, RoboFlow API was applied for learning and processing the physical conditions of the current location, and C# along with Microsoft SQL Server programs were used for the development of the web application. With this developed application, the best routing success of genetic algorithms has been tested in solving this complex routing problem, and it is thought to make comparisons by testing the success of meta-heuristic and hyper-heuristic algorithms in future studies.