Optimal routes and aborting strategies of trucks and drones under random attacks
Optimal routes and aborting strategies of trucks and drones under random attacks
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DOI：
10.1016/j.ress.2022.108457
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发表时间：
2022-03
期刊：
影响因子：
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通讯作者：
Rui Yan;X. Zhu;Xiaoning Zhu;Rui Peng
中科院分区：
文献类型：
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作者：
Rui Yan;X. Zhu;Xiaoning Zhu;Rui Peng
本文试图探索随机攻击下卡车和无人机的最优路径和中止策略。该路线考虑了目标的时间窗口、卡车的中止策略和随机攻击，不仅解决了无人机负载小、工作时间短的缺点，而且还可以在应急管理或军事领域进行初步调查，以获取灾害或敌人信息。假设无人机和卡车可能在路线中受到攻击，并且卡车可以根据完成的任务数量和遭受的攻击数量而中止其任务。此外，基于约束规划模型，提出了一种自适应大邻域搜索与最短路径算法相结合的ALNS-SP混合算法，用于求解考虑随机攻击的卡车和无人机车辆路径问题（VRP-TDA）。设计了基于所罗门数据集的测试集，并通过数值实验验证了ALNS-SP算法的性能。
This paper is an attempt to explore optimal routes and aborting strategies of trucks and drones under random attacks. Time windows of targets, aborting strategies of trucks and random attacks are considered in the truck-drone routes, which not only fixes the shortcomings of drones, such as its small load and short working hours, but also conducts a preliminary survey to gain disaster or enemy information in the field of emergency management or military. It is assumed that drones and trucks may be attacked in the route and the truck may abort its task according to the number of tasks finished and the number of attacks suffered. In addition, based on a constraint programming model, this paper proposes a hybrid algorithm named ALNS-SP algorithm combined with the adaptive large neighborhood search and the short-path algorithm to solve the vehicle routing problem with trucks and drones considering random attacks problem (VRP-TDA). A test set based on Solomon datasets is designed and comparative numerical experiments are presented to illustrate the performance of the ALNS-SP algorithm.