Modeling and algorithms for a dynamic multi-vehicle routing problem with Customers' dynamic requests

Aiming at the dynamic changes of customer requirements,vehicles' diversification and open routes in the dynamic vehicle routing problem(DVRP),a two-phase mathematic programming model was presented for the dynamic vehicle routing problem.Corresponding two-phase solutions of "Pre-optimization Route Scheduling" and "Real-time Dynamic Scheduling" were established.And a Hybrid 2-OPT Quantum-Inspired Evolutionary Algorithm(HQEA) for this dynamic problem was proposed.In the HQEA,an encoding method of converting Q-bit representation to integer representation was designed.Every chromosome represented a kind of route.The 2-OPT algorithm was introduced to optimize sub-routes for convergence acceleration.Finally,some examples were tested and were compared with other algorithms.The effectivness of this method was verified by case study and comparing with the other methods.