OPTIMIZATION OF UNMANNED VEHICLE SCHEDULING AND ORDER ALLOCATION

Abstract

With the development of unmanned vehicles from laboratories to commercial logistics distribution, unmanned vehicles are facing prominent problems, such as order allocation, reasonable setting of appointment time windows, and vehicle route optimization. With the campus distribution of Cainiao unmanned vehicles as an example, an appointment order allocation and route planning problem model of unmanned vehicles was constructed to realize efficient order picking and optimize the operating cost. The operation and distribution efficiency of unmanned vehicles before and after planning was compared using the improved genetic algorithm with limits of load and soft time windows as model constraint conditions. Results of the calculation example reflect that the parcel distribution amount under the planned 1 h appointment mode more than doubled that under the current unplanned 1 h appointment mode. Moreover, the operating cost and parcel picking scheme of Cainiao unmanned vehicles under the planned 1 h and 30 min appointment modes are given, providing decision-making reference for enterprises to balance customer satisfaction and unmanned vehicle scheduling.