Optimizing flight equencing and gate assignment considering terminal configuration and walking time

Operating airline hub-and-spoke networks (HSN) rather than direct flights among city pairs may significantly reduce supplier cost; however, passengers' travel time may significantly increase due to increased transfer and in-flight time. The costs considered in this study are hub-related and incurred by passengers and aircraft (i.e., passenger transfer, flight dwelling, and gate occupancy). The objective is to minimize the total cost by optimizing flight sequence (i.e., arrivals and departures) and gate assignment, while considering transfer speed, transfer demand, flight size, gate size and terminal configuration. A real-world HSN whose hub airport (HA) is located at Xianyang International Airport (XIY) in Xi'an, China is analyzed. The optimized solutions and their relations to various model parameters are explored.     

翼尖尖点散射特性分析

为解决机翼翼尖等弱散射源所带来的雷达散射截面(RCS)贡献问题，针对典型机翼设计了几种不同的机翼翼尖方案，建立了典型翼尖数值模型。利用基于多层快速多极子算法（MLFMA）的FEKO软件，计算、分析不同方案翼尖外形在不同频段、不同方位角下的RCS量级，并优选出对机翼RCS贡献最低的翼尖外形方案。计算结果表明，针对典型机翼，从翼尖到翼根方向上15%处顺气流直切的翼尖外形方案，其翼尖尖点所带来的RCS贡献最小。     

自适应变步长的动量项盲源分离方法

针对传统盲源分离算法采用单一步长而无法同时兼顾收敛速度与稳态性以及动量因子选取的问题，介绍了一种盲源分离优化方法。该方法依据自然梯度算法(Natural Gradient Algorithm，NGA)的收敛条件，通过输出信号建立一种新的表示信号分离程度的度量指标，通过此度量指标构造非线性单调函数，使步长与动量因子参数自适应调节，从而可以合理、准确地选择参数。仿真表明了在平稳和非平稳环境下所提分离指标的正确性，且该指标可有效监测信号分离程度；针对步长及动量因子参数选取所设计的优化策略能够有效地缓解固定值对算法性能的约束，在有无噪声的情况下，均获得了优良的分离效果。     

一种改进的跳频信号参数估计方法

针对在跳频信号跳变时刻和跳变频率估计方面实时性和估计精度无法同时兼顾的问题，提出了一种基于短时傅立叶变换(STFT)和多重信号分类(MUSIC)算法的跳频信号参数估计方法。在建立跳频信号数学模型的基础上，利用STFT选取较大时间窗对整个信号在时域进行粗搜索，生成时频谱图，提取时频脊线从而获得跳变时刻，然后选取较小时间窗在已知跳变时间段利用STFT进行跳变时刻的细估计，并利用MUSIC算法进行频率的精确估计。该方法利用STFT的二次估计，减少了MUSIC搜索范围，从而降低了时间开销。仿真表明该算法的跳变时刻频率估计精度高，实时性能满足参数测量需求。     

敏捷成像卫星快速需求筹划算法

敏捷成像卫星需求筹划主要解决如何判断敏捷卫星对地观测需求是否可执行以及何时执行的问题。首先，根据敏捷卫星对地观测的约束和特点，将敏捷卫星对地观测场景抽象成基于力学的理想弹簧系统，提出了常量机动时间和劲度系数的计算方法，实现模型关键参数的映射；然后，提出了一种启发式算法，利用理想弹簧系统的平衡状态时对应观测综合角度和最小的特点，通过计算系统的力平衡状态求解多个观测需求的整体最佳观测时间；最后，利用实际的观测需求，通过仿真对比验证了算法的有效性。仿真结果显示，所提算法提高了观测需求满足率和需求的优先级权重和，并且整体成像质量最优。     

Optimizing a bi-objective inventory model of a three-echelon supply chain using a tuned hybrid bat algorithm

This paper presents a bi-objective VMI problem in a single manufacturer-single vendor multi-retailer (SM-SV-MR) supply chain, which a redundancy allocation problem is incorporated. In the hybridized problem, a manufacturer produces a single item using several machines that work in series, and stores it in a warehouse to replenish one vendor who delivers it to several retailers using the shortest possible route. A novel meta-heuristic, called hybrid bat algorithm (HBA), with calibrated parameters is utilized to find a near-optimum solution. To show the efficiency of HBA, the results are compared to the ones using the traditional BA and a genetic algorithm.     

公共交通中的数据结构算法与实现分析

近年来,我国城镇化速度不断加快,城市人口不断增多,交通拥堵问题日益突出。公交是城市交通的主力军,通过这一主力军来解决城市交通拥堵问题是必由之路,因此公交数据结构算法与实现问题就显得极其重要。现以GIS为基础,公交数据结构模型为出发点,具体论述了公交数据结构算法与实现的思路,其中包括影响公交数据结构算法与实现的因素,人性化的公交数据结构算法与实现,公交数据结构算法与实现的基本步骤。希望能对缓解城市交通压力问题提供一些借鉴。     

Diverse task scheduling for individualized requirements in cloud manufacturing

Cloud manufacturing (CMfg) has emerged as a new manufacturing paradigm that provides ubiquitous, on-demand manufacturing services to customers through network and CMfg platforms. In CMfg system, task scheduling as an important means of finding suitable services for specific manufacturing tasks plays a key role in enhancing the system performance. Customers’ requirements in CMfg are highly individualized, which leads to diverse manufacturing tasks in terms of execution flows and users’ preferences. We focus on diverse manufacturing tasks and aim to address their scheduling issue in CMfg. First of all, a mathematical model of task scheduling is built based on analysis of the scheduling process in CMfg. To solve this scheduling problem, we propose a scheduling method aiming for diverse tasks, which enables each service demander to obtain desired manufacturing services. The candidate service sets are generated according to subtask directed graphs. An improved genetic algorithm is applied to searching for optimal task scheduling solutions. The effectiveness of the scheduling method proposed is verified by a case study with individualized customers’ requirements. The results indicate that the proposed task scheduling method is able to achieve better performance than some usual algorithms such as simulated annealing and pattern search.     

应用二次过滤模型的干扰任务分配

针对自卫电子对抗中干扰任务分配对资源使用效率的问题，以“一对一”干扰为例，首先构建了干扰任务分配流程，并建立任务程度模型与干扰任务过滤模型，通过二次过滤筛选得到对我方威胁度大且能够被有效干扰的目标；然后根据节约干扰资源的原则，建立以总干扰功率最小为目标函数的干扰任务分配模型；最后采用二进制GPSO（Genetic-Particle Swarm Optimization）算法进行求解，提高了得到最优解的收敛速度、精度以及全局搜索能力。仿真表明，提出的干扰任务分配模型可以较好地筛除威胁程度低及干扰程度小的目标，节约了不必要的资源从而提高了资源的利用率。     

基于BP算法的企业经营状况评价模型

利用2008年的64家公司的数据构建了以每股收益、每股净资产、净资产收益率、主营利润增长率为主的企业经营状况的指标体系,并通过matlab软件建立了基于BP算法的企业经营状况的评价模型。最后利用该模型对2009年的17家公司的经营状况进行了评价,仿真结果表明,基于BP算法的企业经营状况评价模型是一种非常有效的评价方法。