无人机
计算机科学
任务(项目管理)
卡车
布线(电子设计自动化)
有效载荷(计算)
启发式
可变邻域搜索
数学优化
计算
车辆路径问题
变量(数学)
构造(python库)
实时计算
分布式计算
交付性能
下降(航空)
订单(交换)
算法设计
混合算法(约束满足)
匹配(统计)
搜索算法
元启发式
网络数据包
最优化问题
线性规划
任务分析
作者
Xiaoshan Bai,Baode Li,Jianqiang Li,Zongze Wu,Weidong Zhang,Shuzhi Sam Ge
标识
DOI:10.1109/tro.2025.3629808
摘要
As the demand for efficient parcel delivery continues to grow in the logistics industry, optimizing multi-robot task assignment has become crucial for enhancing overall delivery performance. This paper addresses the precedence-constrained multi-truck multi-drone package delivery task assignment problem, where each truck coordinates with a drone to serve multiple dispersed customers under precedence constraints that specify the required order of service. While trucks deliver packages to designated customers, drones can simultaneously serve other customers, subject to their limited flight endurance and payload capacity. To tackle this challenge, a three-phase heuristic algorithm is proposed to minimize the total delivery time required to serve the last customer while ensuring all precedence constraints are satisfied. In the first phase, an extended minimum marginal cost algorithm is applied to quickly construct truck-only routes that comply with precedence constraints. In the second phase, a splitting algorithm combined with an endurance checking procedure is employed to generate hybrid truck–drone routes considering drone limitations. In the final phase, a variable neighborhood descent approach is introduced to further improve the solution by strategically perturbing the truck-only routes. Extensive simulations and experiments demonstrate that the proposed three-phase heuristic algorithm consistently achieves higher-quality solutions with reduced computation time compared with the widely used adaptive large neighborhood search method.
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