A Fuzzy Receding Horizon Control Strategy for Dynamic Vehicle Routing Problem

Abstract

The receding horizon control (RHC) combining with the various intelligent algorithms is a common method for the dynamic vehicle routing problem (DVRP). However, the traditional RHC only considers the objects within each time window while making route plan, and can't make adjustment according to the situations of the objects near the window. In order to deal with this problem, a fuzzy receding horizon control strategy (FRHC) is proposed. By combining the RHC and the membership function theory, the relationship between objects and time window is redefined. And the travel routes are planned by the genetic algorithm (GA) for each fuzzy time window. Finally, ten instances are selected from the DVRP standard test library to verify the proposed strategy. The experimental results show that when comparing with the RHC strategy, the FRHC can reduce the distance, the waiting time of all customers and the number of waiting customers dramatically. The FRHC combines with the GA (FRHC-GA) method is also reasonable and effective.