移动群智感知系统中基于离散布谷鸟搜索算法的任务分配

针对移动群智感知系统中工人积极性低以及任务过期的问题，提出了基于初始成本和软时间窗的任务分配算法。对应的任务分配问题为NP-hard问题，不存在计算有效的最优算法，因此，基于离散布谷鸟搜索算法（DCSA）进行求解。首先，根据问题特征，分别设计了对应的全局搜索过程以及局部搜索过程。其次，根据任务与工人起始位置的距离以及时间窗大小，分析其优先级以便得到更好的解。最后，执行可行化操作，使各次任务分配均满足相关约束。仿真结果表明，与遗传算法和贪婪算法相比，基于DCSA的任务分配算法能够提升工人的参与积极性，解决任务过期的问题，并最终降低系统的总成本。

Task assignment based on discrete cuckoo search algorithm in mobile crowd sensing system

Considering the problems of low-enthusiasm workers and task expiration in the mobile crowd sensing system, a task assignment algorithm based on initial cost and soft time window was proposed. As the corresponding task assignment problem belongs to the category of NP-hard problems and the computationally efficient optimal algorithm cannot be found, thus, an algorithm was developed based on Discrete Cuckoo Search Algorithm (DCSA). Firstly, the corresponding global search process and local search process were designed respectively according to the problem characteristics. Secondly, to derive the better solution, the priorities of tasks with respect to the distance between tasks and workers' starting positions as well as the size of time windows were analyzed. Finally, feasible operations were executed to guarantee that the related constraints were satisfied by each task assignment. Compared with genetic algorithm and greedy algorithm, the simulation results show that DCSA-based task assignment algorithm can improve the enthusiasm of workers to participate, solve the problem of task expiration, and ultimately reduce the total system cost.