不确定环境下的地震应急救援路径优化研究

针对地震应急救援的特点,引入不确定理论,在地震灾害的背景下,研究震后动态网络环境下的应急救援路径选择问题。用不确定变量表示网络中各路段的破坏程度,综合考虑路径破坏程度及车辆路径连续性等约束条件,以救援时间最短为目标,基于不确定理论建立了动态优化模型,并用改进的遗传算法求解,最后设计算例验证了模型和算法的有效性。     

Searching for empirical linkages between demographic structure and economic growth

Demographic structure could affect economic growth through many channels. However, little is known about how demographic structure affects economic growth since no study has examined an extensive collection of channels through which demographic structure could affect economic growth in a single context. This paper overcomes this limitation by examining 45 potential mediating variables between demographic structure and economic growth. A causal search algorithm is used to identify channels through which demographic structure affects economic growth. Our results suggest that demographic structure affects economic growth differently between developed and developing countries. For developed countries, we find that an increase in the share of middle-aged workers has a positive effect on economic growth through institutions, investment and education channels. On the other hand, an increase in the share of the senior population has a negative effect on economic growth through institutions and investment channels. For developing countries, we find (but with weak evidence) that an increase in the share of young workers has a negative effect on economic growth through investment, financial market development and trade channels.     

基于成本优化的制造业生产物流装配线排序问题分析

为了降低制造业的生产成本，提高收益，在分析生产物流配线闲置和超载成本的基础上，采用粒子群算法对其进行优化，并利用模糊自适应改进惯性权值，通过实证研究表明该方法实用，可操作性强，可以有效降低制造业生产物流成本，具有广泛的应用价值。     

Numerical Maximisation of Likelihood: A Neglected Alternative to EM?

There is by now a long tradition of using the EM algorithm to find maximum‐likelihood estimates (MLEs) when the data are incomplete in any of a wide range of ways, even when the observed‐data likelihood can easily be evaluated and numerical maximisation of that likelihood is available as a conceptually simple route to the MLEs. It is rare in the literature to see numerical maximisation employed if EM is possible. But with excellent general‐purpose numerical optimisers now available free, there is no longer any reason, as a matter of course, to avoid direct numerical maximisation of likelihood. In this tutorial, I present seven examples of models in which numerical maximisation of likelihood appears to have some advantages over the use of EM as a route to MLEs. The mathematical and coding effort is minimal, as there is no need to derive and code the E and M steps, only a likelihood evaluator. In all the examples, the unconstrained optimiser nlm available in R is used, and transformations are used to impose constraints on parameters. I suggest therefore that the following question be asked of proposed new applications of EM: Can the MLEs be found more simply and directly by using a general‐purpose numerical optimiser?     

The trade-off between fixed vehicle costs and time-dependent arrival penalties in a routing problem

This paper introduces the vehicle routing problem with soft time windows (VRPSTW) in which problem definition differs from ones previously defined in literature. Branch-and-price approach is employed, resulting in a set partitioning master problem and its new subproblem. Novel techniques are consequently developed to solve this new subproblem. Experimental results report the comparisons of these solution techniques under the branch-and-price framework. The VRPSTW solutions have further been compared to the state-of-the-art literature, signifying the superiority of the VRPSTW on this issue.     

基于遗传算法的锅炉水位控制器设计

文章分析了锅炉水位控制系统的基本原理及结构,针对传统PID控制器的不足之处设计了基于遗传算法的新型锅炉水位控制器,在此基础上搭建了锅炉水位控制系统。最后,通过仿真验证了该水位控制器在改善水位系统稳态误差及动态超调方面均具有较好的作用。     

单车场无时间窗甩挂运输车辆调度的启发式算法

考虑了牵引车空驶、带空挂车行驶和带重挂车行驶所引起的成本差异，定义了牵引车运行成本的概念，将总运行成本最小作为调度方案优劣的判别指标，并同时考虑牵引车数量最少。将牵引任务分为四种类型，定义了任务链、虚拟任务、链内交叉和链间交叉的概念，提出了一种求解该类单车场甩挂运输车辆调度无时间窗约束的启发式算法，包括初始调运方案、链内优化、空车调运交叉、牵引车数量优化和链间交叉。最后给出了仿真算例，算法优化后的最终方案与初始方案相比，牵引车数量减少，总运行成本降低，验证了算法的有效性和可行性。     

Dually sustainable urban mobility option: Shared-taxi operations with electric vehicles

Electric vehicles (EVs) are energy efficient and often presented as a zero-emission transport mode to achieve long-term decarbonization visions in the transport sector. The implementation of a sustainable transportation environment through EV utilization, however, requires the addressing of certain cost and environmental concerns such as limited driving range and battery-charging issues before its full potential can be realized. Nevertheless, a specific type of use of EVs, namely in taxi services, may elicit positive public opinion, as it promises a commitment toward sustainability in urban life. In light of this, this study proposes an integrated approach that combines EV operation with a conceptual design for shared-ride taxi services. As some productivity loss may be naturally expected due to the time spent in charging, it is important to look at whether such performance loss from the passenger and system standpoints can be offset with ingenuity in operational design. In this study, an EV taxi charge-replenishing scheme that can be coupled with a real-time taxi-dispatch algorithm is designed. The proposed EV charging schemes for taxi services are studied via simulations and the effects of the limited driving range and battery-charging details are examined from a system performance viewpoint. The simulation study also reveals illustrative results on the impact of the EV taxi fleet's operation on the charging system. Next, a real-time shared-taxi operation scheme that allows ride sharing with other passengers is proposed to maximize the operational efficiency. The simulation results suggest that the shared-taxi concept can be a viable option to improve on the limitations caused by EV operation. In addition, the importance of projected charging demands and queue delays at different charging locations are also addressed. Some limitations and a future research agenda are also discussed.     

基于PCA-BP-GA的BOT项目风险预测研究

由于BOT项目本身的长期性和复杂性,所以在BOT项目实施前需要准确科学的预测出所面临的风险大小。针对BOT项目风险影响因素众多的问题,先利用主成分分析法进行降维,然后利用遗传算法找出BP神经网络的最优全值阈值,建立了PCAGA-BP BOT项目风险预测模型。同时将以往的BOT项目数据作为学习样本,对BOT项目风险进行预测,并利用某地污水厂的例子进行验证,说明此模型对实际工程的科学指导性。     

基于改进指纹聚类的WLAN定位优化方法

将K-means聚类算法应用到无线局域网（WLAN）位置指纹定位中，虽然可以缩短定位时间，但是容易降低定位精度。为了解决此问题，提出了基于改进指纹聚类的WLAN定位优化方法。首先根据接收信号强度标准差来优化初始聚类中心的选取,然后对指纹数据进行聚类处理,最后进行在线定位。实验结果表明，与传统的WLAN位置指纹定位方法和K-means聚类定位方法相比，基于改进指纹聚类的定位优化方法不仅缩短了定位时间，还能有效提高定位精度。