In recent years, there are many research achievements in the fields of logistics and Unmanned Aerial Vehicle (UAV). But the research achievement of the combination of the two fields is few. Researching on the combination of the UAV filed and the logistics filed has theoretical significance. Effective logistics system and task assignment strategy play an important role in reducing the operation cost of logistics enterprise as well as improving transport efficiency. In this paper, according to the Vehicle Routing Problems with Time Windows (VRPTW), we establish the model of task assignment for UAV in logistics. This model takes multi-constraints (such as weight coefficients, time-windows constraints, the constraints of the UAV and so on ) into account. And then the task assignment problem with multiple constraints is solved by improved Particle Swarm Optimization (PSO) algorithm which is suitable for solving complex combinatorial optimization problems. Meanwhile, we make some modification for the PSO to suit for the acquirement of mutually exclusive. The basic principle and simulation steps of the improved PSO algorithm is described in detail. And a simulation example is given. Furthermore, we compare PSO with Genetic Algorithm. The simulation results show that this algorithm is efficient to solve the problem of task assignment for UAV.
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Jiang et al. (2017) studied this question.