Model and algorithm of vehicle routing problem with time windows in stochastic traffic network

Assigning and scheduling vehicle routes in stochastic traffic network is a crucial management problem. Vehicle routing problem (VRP) is a combinational optimization problem, it belongs to the NP-hard problem theoretically. VRP with time windows and capacity constraint in stochastic traffic network was studied considering the state of traffic network changing randomly under the action of external factors. Multi-objective chance-constrained model was established based on the travel time which was expressed as a random variable according to previous collected data, and modified genetic algorithm for the model was proposed to obtain the optimal vehicle routing corresponding to practice. At last, numerical results were provided to demonstrate the feasibility and validity of the proposed model and algorithm.