Abstract In this study, we discuss the solution to the vehicle routing problem for a heterogeneous fleet with a depot and a time window satisfied by meeting customer demands with various constraints. A 3-stage hierarchical method consisting of transportation, routing, and linear correction steps is proposed for the solution. In the first stage, customer demands have the shortest routing. They were clustered using the annealing simulation algorithm and assigned vehicles of appropriate type and equipment. In the second stage, a genetic algorithm was used to find the optimal solution that satisfies both the requirements of the transported goods and the customer requirements. In the third stage, an attempt was made to increase the optimality by linear correction of the optimal solution found in the second stage. The unique feature of the application is the variety of constraints addressed by the problem and the close proximity to real logistics practice.

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