Parameter Setting Problem in the Case of Practical Vehicle Routing Problems with Realistic Constraints

Vehicle Routing Problem (VRP) is the process of selection of the most favorable roads in a road network vehicle should move during the customer service, so as such, it is a generalization of problems of a commercial traveler. Most of the algorithms for successful solution of VRP problems are consisted of several controll parameters and constants, so this paper presents the data-driven prediction model for adjustment of the parameters based on historical data, especially for practical VRP problems with realistic constraints. The approach is consisted of four prediction models and decision making systems for comparing acquired results each of the used models.