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针对应急条件下高空飞艇(HAA)对地成像观测任务调度问题进行研究,分析了问题中的主要约束条件,建立了以任务收益(TB)和巡航距离为优化目标的约束满足问题(CSP)模型。考虑飞艇侦察载荷具有侧摆观测能力,在构建视场范围约束模型和分辨率约束模型的基础上,对成像观测任务进行合成。提出了元任务与合成任务的概念,给出了任务合成的步骤与方法。将HAA应急调度问题转换为车辆路径问题(VRP),并进一步分解为任务排序主问题和路径选择子问题,分别应用改进粒子群(IPSO)算法和关键节点搜索(KNS)算法求解。详细介绍了算法中的编码、解码和移动等操作,以及采用的混沌初始化和禁忌搜索(TS)策略。通过仿真实验,对文中所提方法的有效性进行了验证。
Aiming at the problems of HAA imaging task scheduling under emergency conditions, the main constraints of the problem are analyzed, and the constraint satisfaction problem (CSP) model is established with the task benefits (TB) and cruise distance as the optimization objectives . Considering that the airship reconnaissance load has lateral observational ability, the imaging observation task is synthesized on the basis of constructing the constraint model of the field of view and the resolution constraint model. Proposed the concept of meta-task and synthetic task, given the steps and methods of task synthesis. The HAA emergency scheduling problem is transformed into the vehicle routing problem (VRP), and further divided into the task scheduling problem and the path selection sub-problem, which are respectively solved by the improved particle swarm optimization (IPSO) algorithm and the key node search (KNS) algorithm. The algorithms of encoding, decoding and moving are introduced in detail, as well as the chaos initialization and tabu search (TS) strategy. Through the simulation experiment, the effectiveness of the proposed method is verified.