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数学优化
整数规划
计算机科学
分解
任务(项目管理)
线性规划
计算
整数(计算机科学)
自由度(物理和化学)
最优化问题
算法
数学
工程类
物理
系统工程
程序设计语言
生物
量子力学
生态学
作者
Mehdi Alighanbari,Yoshiaki Kuwata,Jonathan P. How
标识
DOI:10.1109/acc.2003.1242572
摘要
This paper describes methods for optimizing the task allocation problem for a fleet of unmanned aerial vehicles (UAVs) with tightly coupled tasks and rigid relative timing constraints. The overall objective is to minimize the mission completion time for the fleet, and the task assignment must account for differing UAV capabilities and no-fly zones. Loitering times are included as extra degrees of freedom in the problem to help meet the timing constraints. The overall problem is formulated using mixed-integer linear programming (MILP), which gives the globally optimal solution. An approximate decomposition solution method is also used to overcome the computational issues that arise when using MILP for larger problems. The problem is also posed in a way that can be solved using Tabu search. This approach is demonstrated to provide good solutions in reasonable computation times for large problems that are very difficult to solve using the exact or approximate decomposition methods.
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