基于改进人工鱼群算法的航班进近服务优化

为了减少管制员的工作量,需要对航班进近的服务次序进行优化,建立使得进近管制员的总服务时间最少的数学模型,降低管制员的工作负荷,减少平均航班延误量。以改进的人工鱼群法为核心算法,结合概率当中的＂捆绑法＂思想以及先到先服务原则,形成综合算法。仿真结果表明,此综合算法能减少航班平均延误,减少空中交通服务时间,从而减少管制员的工作量。     

基于STW-GA算法的离港航班调度优化模型

为缓解离港航班延误现状,减少航班延误带来的损失,研究了离港航班优化调度问题.建立了最小化航班延误成本、最小化航班位移量和最小化机位占用时间的多目标优化模型,将遗传算法与滑动时间窗相结合对模型进行求解,仿真结果表明,与先到先服务(FCFS)相比,航班延误损失减少35.5％,且延误损失在各航班之间的分配更加均衡,可见所提优...     

机场流量管理模型的公平性与有效性研究

为了使协同式地面延误程序(CDM GDP)中的时隙分配更趋于合理化，本文先对该程序中基于OPTIFLOW模型的时隙分配(RBS )算法和时隙分配的公平性一有效性(E—E)标准选取进行了理论分析，并根据理论分析的结果进行了实验仿真，得出了各个航班的延误时间和所有航班的总延误成本的分布。仿真结果表明：当采用航班单优先权方法作为E—E标准时，既能有效减少总延误成本，同时还能兼顾公平性因素，是一种比较理想的E—E标准。     

基于Petri网的航班运行建模和延误波及分析

针对当前缺乏面向航班延误波及分析的精确航班运行模型、以及延误波及分析算法复杂度过高的不足,提出一种航班运行时间Petri网模型及延误波及分析算法。该模型对库所和变迁分别赋予时间区间约束,可精确描述航班机场过站时间以及航班飞行时间等关键性航班特征;同时,利用线性逻辑推理能力对所建模型进行约简,分别导出变迁和变迁序列的顺序激发规则,并在此基础上提出具有实时性的航班延误波及分析算法。考虑飞机起飞源机场不同的初始延误水平,建立相应模型并分析航班延误波及,结果表明,所给模型和算法能够有效预测航班在下游机场是否延误并快速给出延误水平。     

不正常航班优化调度方法研究

本文提出了采用分层调度的策略对不正常航班调度进行处理,通过确定不同延误范围的门限,分层次采用相应的调度策略,并使用蚁群算法快速求解,既满足对航班延误状况的有效调度处理,又可以兼顾综合时间成本。通过对航空公司数据进行延误仿真测试表明,本策略是能够覆盖各种范围的延误状况处理,同时也能够达到较好降低综合时间成本的处理效果。     

大面积航班延误下停机坪保障调度研究

针对大面积航班延误下的停机坪保障作业调度问题,考虑航班延误数量、航班延误总时间和各保障设备的作业均衡性,构建大面积航班延误下停机坪保障调度模型,并基于保障设备工作的迫切度和航班被保障的需求强烈度,求解大面积延误下停机坪保障调度模型,实例分析显示,本算法可有效减小设备的等待时间,提高保障设备的运行效率,进而降低航班的延误次数和延误时间。     

航站楼离港航班动态性仿真研究

研究航站楼仿真,可以为机场的决策者提供决策依据,提高机场的运行效率,减少延误并提高服务质量。本文在计算机仿真软件ServiceModel中采用正常航班时间窗口内随机产生的离港时间,对离港航班仿真建模。仿真结果体现了离港航班的动态性。     

飞机进场排序的研究

为了缓解空中交通延误问题,提高机场运行效率,我们采用遗传算法优化进场飞机的序列,分别考虑单跑道和双跑道排序两种情况,运用运筹学约束最优化方法及目标规划,分别建立单跑道和双跑道两种排序优化模型,将仿真结果与先到先服务算法相比较,结果表明,对于单跑道模型而言,总延误时间减少了15.8％,对于双跑道模型而言,总延误时间减少了50％,适应度增加了83％,说明遗传算法可以极大地优化进场飞机队列,从而减少飞机序列的总延误时间.     

航路资源分配下的航班时刻优化

本文分析了航路资源合理分配的必要性,以航路上所有航班的总延误成本最小为目标函数,以航班时刻变动范围、时刻数量和航路容量限制为约束条件,建立了航路耦合容量模型和航班延误成本模型。再以京-沪航路航班数据为基础进行算例分析,运用匈牙利算法求解模型。计算结果表明:新增了10个航班时刻;缩短了11个航班的延误时间;优化后航班最小总延误成本明显降低。通过改航到临时航线,使其利用率提高了43.5%;各飞行航段的实时流量与容量限制更加匹配,降低了空中交通延误时间。     

航班延误原因及措施研究

随着我国民航业的快速发展,飞机出行正成为人们出行的主要方式。民航的飞速发展导致航班延误情况时有发生,航班延误不仅对航空公司的运行效率和服务质量产生负面影响,同时会耽误乘客的时间,严重扰乱机场秩序,甚至可能引发航空安全事故。本文分析了航班延误的主要原因,根据当前航班延误存在的问题进行探讨,提出了应对航班延误措施的几点建议。     

人工免疫算法规划复杂环境下三维飞行航迹

应用人工免疫算法规划复杂地形和火力威胁环境下的三维飞行航迹.根据实际地形的特点提取在山岭横栏的地形和多火力威胁包围的复杂场景,利用人工免疫算法的3种情况分别进行飞行器的航线设计,同时根据飞机的机动性和适航性对上述规划出的航迹进行优化;并把免疫算法3种情况的模拟结果进行比较.仿真结果表明,与遗传算法相比,人工免疫算法在规划复杂环境下三维航迹是可行的,在时间上有一定的优势.     

相空间重构参数选择方法的研究

基于目前相空间重构中常用的参数选择方法,提出了一种新的相空间重构的联合算法,联合算法以时间窗口法和互信息法为基础,在综合考虑嵌入窗宽的基础上,可同时确定嵌入延迟和嵌入维数.仿真实验表明,用该算法计算Lorenz混沌时间序列关联维相对误差由传统算法的0.83%降低到0.44%,有效地提高了计算相空间重构中不变量的精度.     

Multi-missile interception for multi-targets: Dynamic situation assessment,target allocation and cooperative interception in groups

Target allocation is a crucial point in the cooperative interception process. In this paper, a new algorithm of dynamic situation assessment, target allocation and cooperative interception in groups is proposed for multi-target interception with multiple missiles. An effective situation assessment function is proposed, according to which the targets of each intercepting missile are assigned to maximize their efficiency. The new situation assessment function evaluates the flight status and cooperation of missiles, which considers not only the relative position and velocity mentioned in traditional functions, but also relative normal velocity, normal acceleration, maneuverability and cooperation between multiple missiles. During the interception process, the flight status could be evaluated dynamically, thus the allocation of the missiles could be real-time adjusted. To optimize target allocation, a method based on genetic algorithm is applied, which uses the dynamic situation assessment function based proportional navigation guidance law, and we also use proportional navigation guidance law to realize the interception to maneuvering targets with multiple missiles. Simulations for target allocation and target interception validate the effectiveness of the algorithm. Potential adjustments and improvements are proposed according to the simulation results.     

不正常航班恢复模型的贪婪模拟退火算法研究

为解决不正常航班恢复对航空公司带来的严重影响,研究了不正常航班恢复模型及其优化算法,对现有不正常航班恢复优化模型提出适当改进,重点设计了一种贪婪模拟退火算法。算法融合了GRASP和模拟退火算法的特点,提高了领域解的选择效率并且降低了陷入局部最优解的概率。实例证明这种算法可以处理大规模的不正常航班恢复问题,并且能够达到时间代价与结果质量的均衡。     

基于LPV近空间飞行器的快速故障估计

针对临近空间飞行器的纵向飞行的非线性模型,首先利用线性变参数系统的思想对高超声速飞行器模型进行线性化;其次,考虑在执行器故障发生的情况下,基于LPV建立NSV线乘性故障模型,进而引入一种快速自适应故障估计的算法,并与传统的自适应估计算法相比较,最后仿真验证快速故障估计算法能够大大减少故障估计的时间和提高估计的精度.     

Optimized scheduling of resource-constraints in projects for smart construction

In real-life applications, resources in construction projects are always limited. It is of great practical importance to shorten the project duration by using intelligent models (i.e., evolutionary computations such as genetic algorithm (GA) and particle swarm optimization (PSO) to make the construction process reasonable considering the limited resources. However, in the general EC-based model, for example, PSO easily falls into a local optimum when solving the problem of limited resources and the shortest period in scheduling a large network. This paper proposes two PSO-based models, which are resource-constrained adaptive particle swarm optimization (RC-APSO) and an input-adaptive particle swarm optimization (iRC-APSO) to respectively solve the static and dynamic situations of resource-constraint problems. The RC-APSO uses adaptive heuristic particle swarm optimization (AHPSO) to solve the limited resource and shortest duration problem based on the analysis of the constraints of process resources, time limits, and logic. The iRC-APSO method is a combination of AHPSO and network scheduling and is used to solve the proposed dynamic resource minimum duration problem model. From the experimental results, the probability of obtaining the shortest duration of the RC-APSO is higher than that of the genetic PSO and GA models, and the accuracy and stability of the algorithm are significantly improved compared with the other two algorithms, providing a new method for solving the resource-constrained shortest duration problem. In addition, the computational results show that iRC-APSO can obtain the shortest time constraint and the design scheme after each delay, which is more valuable than the static problem for practical project planning.     

一种新的动态时隙混合类网络通讯协议

提出一种新的动态时隙混合类MAC协议——CA-QC协议。CA-QC协议能够在控制时隙内集中消除所有的接入冲突,并提出消费算法来提高实时业务的QoS保障,然后通过队列管理算法来实现整个网络完全分布式运行。仿真结果表明,对于时延敏感的实时业务,CA-QC协议可以提供有效支持,并可在混合业务环境下,在接入时延和接入效率方面呈现出较好性能。     

Stability and bifurcation of delay-coupled genetic regulatory networks with hub structure

In this paper, we study the local stability and bifurcation of a delay-coupled genetic regulatory networks consisting of two modes with the hub structure. By analyzing the equilibrium equation, the number of the positive equilibria is discussed in both the cases that there are inhibition coupling and activation coupling in the networks. It is revealed that multiple equilibria could exist in the developed genetic networks and the number of the equilibria could be distinct under the two cases of delayed-coupling. For the equilibrium, the conditions of the coupling-delay-independent stability and the saddle-node bifurcation are derived with respect to the biochemical parameters. The coupling-delay-dependent stability and the Hopf bifurcation criteria on the biological parameters and the coupling delay are also given. Moreover, the complexity of the algorithm used in this paper is analyzed. The numerical simulations are made to certify the obtained results. The multistability of the developed genetic regulatory networks is displayed. The different effects of the coupling delay on the stability of the genetic networks under different biochemical parameters are shown.     

Stabilization criteria for neutral time delay systems with saturating actuators

This paper discusses the problems of delay-dependent stability and stabilization of neutral saturating actuator systems with constant or time-varying delays. The problems of stabilization for neutral saturating actuator system with time-varying delay and parameter from the presented results, the condition obtained here does not need derivative information of the delay time and thus can be used to analyze the stabilization problem for a class of saturating actuator systems with time-varying delay, which is bounded but arbitrarily fast time-varying. Using the model transformation and quasi-convex optimization problem, we derive delay-dependent conditions for the stability of systems in terms of the linear matrix inequality. The stabilization conditions are formulated as linear matrix inequalities (LMIs) which can be solved by convex optimization algorithm. Moreover, the stability criteria are extended to design a stabilizing state feedback controller. Numerical examples show that the results obtained in this paper significantly improve the estimate of stability limit over some existing results reported previously in the literature.