Multi-objective Path Planning of Single Delivery Robot in Epidemic Control Campus

In order to improve the delivery efficiency of single delivery robot in the campus environment of epidemic closure and control, in this paper, an MMOEA/D algorithm that combines the multi-objective evolutionary algorithm MOEA/D based on decomposition strategy and local search strategy is proposed. Firstly, the campus environment model is established, and the A* algorithm is used to plan the path matrix between the target points. Then, with the shortest path length and the shortest average delay time as the goal, the MMOEA/D algorithm is used to determine the traversal sequence of each target point to get the best path. In this paper, MMOEA/D algorithm is compared with MOEA/D algorithm and NSGA-II algorithm. The experimental results show that the target value and path optimized by the MMOEA/D algorithm is better.