<br>具有时间耦合约束的多无人机协作任务分配的无死锁混合分布估计算法,IEEE Transactions on Aerospace and Electronic Systems

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具有时间耦合约束的多无人机协作任务分配的无死锁混合分布估计算法
IEEE Transactions on Aerospace and Electronic Systems ( IF 5.1 ) Pub Date : 11-25-2022 , DOI: 10.1109/taes.2022.3224694
Ruipeng Zhang ₁ , Yanxiang Feng ₁ , Yikang Yang ₁ , Xiaoling Li ₂

Affiliation

本文解决了具有时间耦合约束的协作多无人机任务分配问题（CMTAP），旨在找到可行的分配以最小化所有任务的等效距离。我们首先提出了 CMTAP 的混合整数线性规划模型。为了解决CMTAP不良的死锁问题，基于候选解构建了Petri网修正器，无死锁解相当于可以在相应修正器中顺序触发的可行转换序列。通过这个修正器，我们提出了一种基于 Petri 网的死锁修正方法（PDAM），具有多项式时间复杂度，将死锁解决方案转换为无死锁解决方案。此外，通过将 PDAM 嵌入到原始 EDA 中，为 CMTAP 开发了无死锁混合分布估计算法 (DHEDA)。为了进一步提高解决方案质量，我们建立了局部开发方法，并使用自适应操作概率来平衡计算负担和局部开发能力。然后，提出了一种基于匹配的重新分配方法来应对时间敏感的目标。最后，大量的计算实验表明，PDAM 在解决死锁方面比基于图的方法更有效，特别是对于大规模 CMTAP，并且 DHEDA 在解决 CMTAP 时优于现有算法。

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A Deadlock-Free Hybrid Estimation of Distribution Algorithm for Cooperative Multi-UAV Task Assignment With Temporally Coupled Constraints

This article addresses the cooperative multiunmanned aerial vehicles task assignment problem (CMTAP) with temporally coupled constraints and aims to find a feasible assignment to minimize the equivalent distances of all tasks. We first present a mixed-integer linear programming model of CMTAP. To solve the undesirable deadlocks of CMTAP, a Petri net amender is constructed based on a candidate solution, and a deadlock-free solution is equivalent to a feasible transition sequence that can be fired sequentially in the corresponding amender. With this amender, we present a Petri net-based deadlock amending method (PDAM) with polynomial time complexity to convert a deadlocked solution into a deadlock-free solution. Also, a deadlock-free hybrid estimation of distribution algorithm (DHEDA) is developed for CMTAP by embedding PDAM into the original EDA. To further improve the solution quality, we establish a local exploitation method, and an adaptive operational probability is used to balance the computational burden and local exploitation ability. Then, a match-up-based reassignment method is proposed to cope with time-sensitive targets. Finally, extensive computational experiments demonstrate that PDAM is more effective at solving deadlocks than graph-based methods, particularly for large-scale CMTAP, and DHEDA outperforms existing algorithms when solving CMTAP.

更新日期：2024-08-28

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