The present application relates to the technical field of intelligent logistics scheduling and transportation path optimization, and discloses a
truck dynamic path and time window optimization method, which is used for solving the problems of instruction failure caused by cloud reconstruction
delay and vehicle continuous displacement asynchronization in traditional methods, and the problems of global rearrangement range expansion and calculation efficiency reduction caused by the fact that local
delay is not effectively isolated; the method firstly establishes a distribution session, uniformly processes vehicle operation data, task data and road network state data, finds future execution position and execution starting node after disturbance occurs, checks
time sequence of subsequent distribution nodes, finds abnormal nodes, and sequentially carries out
time extension absorption, node reorganization,
path reconstruction and terminal confirmation within the local path boundary, completes dynamic path adjustment and version update, and realizes normal operation of
truck distribution scheduling.