Research On Optimization Models And Algorithms For Vehicle Routing Problem Of Simultaneous Pick-up And Delivery With Time Windows

In order to quickly respond to customers,reasonably reduce distribution costs,and avoid the loss of distribution capacity caused by "empty travel" in the process of vehicle distribution,modern logistics companies integrate pick-up and delivery services on the basis of considering customer service time,resulting in the vehicles routing problem of simultaneous pick-up and delivery with time windows(VRPSPDTW).Due to the influence of factors such as customer service time,vehicle load,travel constraints and multi-center joint distribution,it is more difficult to solve VRPSPDTW.Therefore,the study of VRPSPDTW has theoretical significance and engineering application value.The main research work includes:(1)The VRPSPDTW is discussed.In this paper considering one depot,single vehicle type and customer time window,a route optimization model is established to minimize the total cost of vehicle use cost and vehicle driving cost,and an adaptive brain storm optimization is proposed to solve it.The global search stage,using multiple penalty methods to expand the search area,using clustering and three path search strategies for global search;in the local search stage,six kinds of damage-repair operators are used as candidate sets,and then an adaptive dynamic neighborhood search mechanism is designed,to enhance the local search performance.(2)The multi-depot vehicles routing problem of simultaneous pick-up and delivery with time windows based on joint distribution(MDVRPSPDTWJD)is presented.Further consider the VRPSPDTW with multiple distribution centers,establish a total cost minimization optimization model considering fixed costs,variable costs and penalty costs,and propose a variable sparrow search algorithm to solve the problem.Optimize the initial position distribution of the sparrow population through the Sine chaotic mapping function,introduce the sine search strategy to improve the sparrow position update method,improve individual adaptability,and integrate the variable neighborhood search algorithm into the local search strategy of the sparrow search algorithm to improve the overall search efficiency of the algorithm.(3)Example verification and result analysis.Aiming at the VRPSPDTW problem,the standard example test set is selected for simulation experiments,and the validity of the model is verified through the comparison and analysis of small-scale examples,large-scale examples and actual logistics cases,and it is proved that the algorithm in this paper has better performance than existing algorithms.For the MDVRPSPDTWJD problem,the MDVRP example,the VRPSPDTW example and the MDVRPSPDTWJD example are selected for simulation experiments.The results show that the proposed algorithm has better performance,strong stability and robustness.