Dynamic Assignment Model of Terminal Distribution Task Based on Improved Quantum Evolution Algorithm

Most logistics and express delivery enterprises will allocate distribution tasks according to fixed distribution service areas at the end of their distribution business. It is impossible to set up reasonable distribution resources for the dynamic distribution demand that changes frequently and is unevenly distributed, which causes the unbalanced workload of each terminal distribution node and further leads to the distribution scheduling management chaos and other problems. A distribution task assignment model considering distribution cost, resource utilization and workload ratio difference is established to solve the problem of terminal distribution task assignment. The stability of quantum group is adopted as the exit criterion to avoid the problem of early withdrawal and invalid iteration of the algorithm, and the mechanism of quantum variation and elimination is introduced to enhance the search ability of the algorithm for feasible solutions. The experimental results show the scheme presented by the algorithm can effectively alleviate the uneven distribution of distribution tasks and effectively reduce the overall distribution cost that compared with the distribution scheme according to distribution area.