Compatibility themed solution of the vehicle routing problem on the heterogeneous fleet

In today's logistics applications, the constraints of the vehicle routing process have diversified and the routing complexity has gradually increased due to the diversified customer demands and the determined legal requirements. Firms need low-cost but flexible and permanent solutions that will adapt to changing conditions while performing customer deliveries. In this study, the problem of single-warehouse heterogeneous fleet vehicle routing with tight time windows, which occurs when customer demands, which are known to have different types of transportation needs, are met by using a heterogeneous fleet containing vehicles with different capacities and characteristics. A hierarchical three-stage decision support system has been designed to produce new solutions in various situations such as canceled customer requests, closed roads or broken vehicles. In the first stage, customer demands are grouped using the simulated annealing algorithm to have the shortest path distance. While making this grouping, it is aimed that the total distance of each group is balanced, that is, equal. In the second stage, vehicle assignment modeling was used. The customer demands grouped in the first stage were matched with suitable types and features. While performing this matching process, the optimal solution suitable for the problem constraints was investigated with the help of genetic algorithm. In the third stage, the quality of the solution was tried to be increased by linear correction on the optimal solution in the second stage.