对地观测卫星系统部署-调度一体化问题研究

项目名称： 对地观测卫星系统部署-调度一体化问题研究

项目编号： No.71501180

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 管理科学

项目作者： 刘晓路

作者单位： 中国人民解放军国防科技大学

项目金额： 17.4万元

中文摘要： 对地观测卫星系统(EOSS)是当前最主要的太空信息获取平台，其观测效能取决于系统的部署和调度两个方面。部署子问题通过优化卫星的轨道和载荷配置参数实现对系统性能的改进，调度子问题在既定部署方案下通过合理分配和安排卫星资源实现对用户需求的最大化满足，两者互相耦合、互相影响。当前，我国EOSS的部署与调度相互分离，致使系统效能不高。针对此，本项目研究EOSS部署-调度的一体化问题，常规模式下将问题建模为连续空间的高维黑箱优化问题，提出基于代理模型的近似优化方法进行求解；应急模式下将问题建模为双层优化问题，构建了基于遗传算法（GA）和自适应大邻域搜索（ALNS）算法的求解框架，GA用以生成系统的部署方案并将其作为调度问题的输入，ALNS用以实现不同卫星的协同调度，调度结果作为GA适应度函数对部署方案进行评估。本项目提供了一种新的双层优化问题的求解框架，对我国未来对地观测卫星系统的发展具有重要的理论支持。

中文关键词： 部署调度一体化；双层优化；自适应大邻域搜索；代理模型；时间依赖

英文摘要： Earth observation satellite system (EOSS) works as the main space platform acquiring earth images. Its observation performance is determined by two coupled problems of system configuration and scheduling. Problem of system configuration is solved to improve EOSS performance by optimizing orbit and sensor parameters of satellites. Problem of scheduling is to maximize the number of satisfied user requests by reasonably allocate satellites. The two problems are interactively coupled by common variables influencing the observation efficiency of EOSS. EOSS of our country is of low efficiency due to the separation of two problems. Therefore, problem of integrated configuration and scheduling of EOSS is investigated. For regular situation it is taken as a high-dimensional black-box optimization problem in continuous space which is solved by a surrogate model based approximation method. For emergency situation, the problem becomes a bi-level optimization problem. A combined framework of genetic algorithm (GA) and adaptive large neighborhood search (ALNS) algorithm is proposed to solve it. GA is used to generate different system configurations which will work as inputs of EOSS scheduling problem. ALNS will create a schedule so that different satellites can work in a collaborated way. Then the created schedule is fed back to GA as its fitness merit to judge whether the configuration is optimized or not. The acquisitions of this project raise a new method to solve the bi-level optimization problem. At the same time they provide important theoretical supports for the development of future EOSS in our country.

英文关键词： Integrated configuration and scheduling; Bi-level optimization;Adaptive large neighborhood search;Surrogate model;Time dependent