High energy-density propulsion—reducing the risk to humans in planetary exploration

The potential benefits to humankind of space exploration are tremendous. Space is not only the final frontier but is also the next marketplace. The orbital space above Earth offers tremendous opportunities for both strategic assets and commercial development. The critical obstacle retarding the use of the space around the Earth is the lack of low cost access to orbit. Further out, the next giant leap for mankind will be the human exploration of Mars. Almost certainly within the next 30 years, a human crew will brave the isolation, the radiation, and the lack of gravity to walk on and explore the Red planet. Both of these missions will change the outlook and perspective of every human being on the planet. However, these missions are expensive and extremely difficult. Chemical propulsion has demonstrated an inability to achieve orbit cheaply and is a very high-risk option to accomplish the Mars mission. An alternative solution is to develop a high performance propulsion system. Nuclear propulsion has the potential to be such a system. The question will be whether humanity is willing to take on the challenge.     

EUROPEAN NETWORK FOR THE NUMERICAL SIMULATION OF SPACE PLASMAS

The Cluster mission of the European Space Agency (ESA) will allow, for the first time three-dimensional measurements in key regions of the Earth's magnetosphere to be carried out. The European Numerical Simulation Network (ENSN) aims at providing a theoretical support to the mission. We describe the achievements of the ENSN during its first period of activity 1991–1994, during which the network was funded by the European Union. In particular, the ENSN has set up (i) thematic Working Groups on the prime scientific goals of the mission, (ii) a code development Working Group to develop numerical simulation codes specifically adapted to studying magnetospheric boundaries and the corresponding scale mixing, and (iii) software models of Cluster instruments to test in a numerical simulation what the set of four instruments will measure.     

Scientific Planning and Commanding of the Rosetta Payload

ESA’s Rosetta mission was launched in March 2004 and is on its way to comet 67P/Churyumov-Gerasimenko, where it is scheduled to arrive in summer 2014. It comprises a payload of 12 scientific instruments and a Lander. All instruments are provided by Principal Investigators, which are responsible for their operations. As for most ESA science missions, the ground segment of the mission consists of a Mission Operations Centre (MOC) and a Science Operations Centre (SOC). While the MOC is responsible for all spacecraft-related aspects and the final uplink of all command timelines to the spacecraft, the scientific operations of the instruments and the collection of the data and ingestion into the Planetary Science Archive are coordinated by the SOC. This paper focuses on the tasks of the SOC and in particular on the methodology and constraints to convert the scientific goals of the Rosetta mission to operational timelines.     

基于粗集的调度Agent知识库建模研究

首先通过相识集、招标集、投标集和中标者的概念，描述了车间调度系统中的调度Agent与资源Agent间任务分配的招投标关系；运用粗集理论，基于任务的属性和资源Agent完全任务的成本、质量、负荷和时间等属性构造决策表；在分析了决策表的特征基础上，生成调度规则集，即调度知识库；最后给出车间调度Agent的调度过程算法。     

基于并行禁忌遗传算法(PTGA)的预警卫星传感器调度研究

对预警卫星的传感器调度进行了研究，提出了传感器管理调度的系统组成。通过对传感器调度的分析，建立起相应的数学模型，定义了评价指标。结合并行遗传算法和禁忌搜索的特点，提出了一种新的解决预警卫星传感器调度问题的并行禁忌遗传算法(PTGA)。该算法采用多种群和禁忌搜索思想改进遗传算法的性能，从而提高整个算法的收敛速度和精度。实验结果表明该算法有效地解决了多目标情况下的传感器实时调度问题，并优于一般启发式算法。     

卫星图像采集任务调度系统的设计与实现

随着卫星遥感技术的高速发展 ,卫星图像在众多领域有了广泛的应用。文章给出了一个卫星图像采集任务调度系统的总体结构及其功能 ,讨论了该系统实现过程中的卫星资源描述、卫星图像采集任务描述、调度引擎、卫星时间窗口的仿真计算、调度结果的可视化展现等关键技术 ,归纳了系统的特点 ,并总结了今后系统的研究方向     

飞机空中加油任务剖面优化设计

介绍了某型飞机执行作战任务途中何时进行空中加油，并按照最大航程截击对飞机各个飞行任务段的飞行性能进行了计算，得出了最佳巡航速度，确定了最优的加油时机和加油量。计算过程中采用了遗传算法，考虑了爬升过程和巡航过程中飞机变质量的难点问题，提高了计算结果的可信度。     

航班调度应急管理研究

航班调度应急管理是针对频发、突发事件的管理方法,它以提高顾客利益与航空公司利益的综合效应为目标,涵盖了制定航班计划到执行计划的整个过程.本文就航班调度应急管理的两种方法：鲁棒调度与受扰恢复策略,论述了两者的研究重点、数学模型和算法.     

加工时间依赖工件位置的单机成组排序问题

排序问题是一类重要的组合优化问题,现代排序问题突破了经典排序问题的种种假设,有着越来越广阔的应用前景。对加工时间依赖于工件位置的单机成组排序问题进行了研究,讨论了成组技术中,要求同一组内工件必须连续加工,加工时间的函数变量是工件所在的加工位置,目标函数分别为极小化最大完工时间与总完工时间。分别给出其多项式时间的最优算法。     

Online scheduling of distributed Earth observation satellite system under rigid communication constraints

This paper focused on online scheduling of distributed Earth observation satellite system in a dynamic environment. The objective was to maximize the total profit of the overall system by efficiently coordinating the different satellites with stochastic arrival of urgent tasks, subject to rigid communication and observation time window constraints. We formulated this problem as a single-task, single-robot, time-extended assignment problem with intra-schedule dependency using the multi-robot task assignment taxonomy and formulated the sub-problem after releasing urgent tasks in a mixed-integer linear programming model. We first described the online scheduling algorithm for a single satellite, then we proposed the modified consensus-based bundle algorithm (m-CBBA) and modified asynchronous consensus-based bundle algorithm (m-ACBBA) with synchronous and asynchronous communication, respectively. Compared with initial versions of CBBA and ACBBA, the modified versions added the communication loop prediction phases to efficiently utilize scarce communication opportunities and reduce the communication requirements. Additionally, we introduce two contract net protocol (CNP)-based algorithms for comparison, respectively SingleItem-CNP-based (SI-CNP) algorithm and Batch-CNP-based (BA-CNP) algorithm. Computational experiments indicated that both the total profit and percentage of scheduled urgent tasks achieved by the m-ACBBA and m-CBBA algorithms were much higher than those achieved by both SI-CNP and BA-CNP. Additionally, the number of communications needed by either m-ACBBA or m-CBBA algorithm was lower than that by SI-CNP. When the communication cost in the system is high, the m-CBBA algorithm is preferred because it balances the profit and the required number of communications. When the communication cost is low, the m-ACBBA algorithm is preferred because it achieves high total profit and high percentage of scheduled urgent tasks.