Simultaneous Pickup and Delivery Vehicle Route Optimization with Time Windows under Time-varying Road Networks

This study addresses the problem of simultaneous pickup and delivery of urban and rural networks. Big data is used to predict the congestion index of vehicles in different time periods under different road types to calculate the actual travel speed, and a time-varying road network model is established with the goal of minimizing the total cost. An improved adaptive genetic algorithm is designed and its effectiveness is verified by an example. Finally, the impact of traffic congestion level and carbon tax cost on the distribution scheme is discussed through sensitivity analysis. The results show that the improved adaptive genetic algorithm has better solution performance. Traffic congestion will affect speed, which in turn will affect the cost of delivery. The increase in carbon tax will not only affect the cost of carbon emissions but also have a negative impact on other costs and reduce corporate profits.