The hybrid genetic ant colony algorithm (GACM) is applied to solve the VRP problems of oil transportation between oil terminals with significant time and cost. The algorithm for selecting ant colony methods and genetic algorithm is used to determine the optimal tank routes considering various constraints such as tank capacity, time window, and distance. The ant algorithm is responsible for selecting routes considering pheromones and heuristic factors, while the genetic algorithm is used to optimize routes through crossover and mutation, which ensures fast solution search and improved results. The performance of the proposed algorithm was evaluated based on oil terminal networks, where real time windows for unloading and refueling tankers, as well as the cost of distance between terminals and shipments were considered. The results lead to improvements compared to classical optimization methods such as nearest neighbor and greedy algorithms. The proposed hybrid approach allows to significantly reduce the transportation time, as well as reduce the cost of logistics operations, which is a necessary condition in the conditions of the modern oil industry. The use of AGKM can be used to optimize processes in various industries where it is necessary to solve complex routing problems with large number of restrictions.