Optimal Scheduling Scheme for Urban Crowdsourcing Distribution Task Based on Path Planning

Abstract

At present, in the “last mile” urban crowdsourcing distribution process, there are shortcomings such as unreasonable task assignment and unclear distribution path planning, which reduce the distribution efficiency and waste a lot of manpower and time. Aiming at these problems, this paper proposes a task scheduling scheme and mathematically models it. The optimization goal is to minimize the total distribution path length when all tasks are assigned. A variable neighborhood search algorithm (VNS) is designed, four neighborhood operations are constructed, and a selection probability is set for every neighborhood operation to reduce the solution time of the algorithm. In addition, a heuristic solving algorithm (HSA) is implemented as a comparison. The experimental results show that VNS has a higher solution quality in solving the urban crowdsourcing distribution task scheduling problem, and VNS can improve the scheduling efficiency of the urban crowdsourcing task.