Latent temporal preferences: An application to airline travel

An essential element of demand modeling in the airline industry is the representation of time of day demand—the demand for a given itinerary as a function of its departure or arrival times. It is an important datum that drives successful scheduling and fleet decisions. There are two key components to this problem: the distribution of the time of day demand and how preferred travel time influences itinerary choice. This paper focuses on estimating the time of day distribution. Our objective is to estimate it in a manner that is not confounded with air travel supply; is a function of the characteristics of the traveler, the trip, and the market; and accounts for potential measurement errors in self-reported travel time preferences. We employ a stated preference dataset collected by intercepting people who were booking continental US trips via an internet booking service. Respondents reported preferred travel times as well as choices from a hypothetical set of itineraries. We parameterize the time of day distribution as a mixture of normal distributions (due to the strong peaking nature of travel time preferences) and allow the mixing function to vary by individual characteristics and trip attributes. We estimate the time of day distribution and the itinerary choice model jointly in a manner that accounts for measurement error in the self-reported travel time preferences. We find that the mixture of normal distributions fits the time of day distribution well and is behaviorally intuitive. The strongest covariates of travel time preferences are party size and time zone change. The methodology employed to treat self-reported travel time preferences as potentially having error contributes to the broader transportation time of day demand literature, which either assumes that the desired travel times are known with certainty or that they are unknown. We find that the error in self-reported travel time preferences is statistically significant and impacts the inferred time of day demand distribution.     

Integrated optimization on train scheduling and preventive maintenance time slots planning

We address the problem of simultaneously scheduling trains and planning preventive maintenance time slots (PMTSs) on a general railway network. Based on network cumulative flow variables, a novel integrated mixed-integer linear programming (MILP) model is proposed to simultaneously optimize train routes, orders and passing times at each station, as well as work-time of preventive maintenance tasks (PMTSs). In order to provide an easy decomposition mechanism, the limited capacity of complex tracks is modelled as side constraints and a PMTS is modelled as a virtual train. A Lagrangian relaxation solution framework is proposed, in which the difficult track capacity constraints are relaxed, to decompose the original complex integrated train scheduling and PMTSs planning problem into a sequence of single train-based sub-problems. For each sub-problem, a standard label correcting algorithm is employed for finding the time-dependent least cost path on a time-space network. The resulting dual solutions can be transformed to feasible solutions through priority rules. Numerical experiments are conducted on a small artificial network and a real-world network adapted from a Chinese railway network, to evaluate the effectiveness and computational efficiency of the integrated optimization model and the proposed Lagrangian relaxation solution framework. The benefits of simultaneously scheduling trains and planning PMTSs are demonstrated, compared with a commonly-used sequential scheduling method.     

Spatial transferability assessment of a composite walkability index: The Pedestrian Index of the Environment (PIE)

This paper analyzes the transferability of a composite walkability index, the Pedestrian Index of the Environment (PIE), to the Greater Montréal Area (GMA). The PIE was developed in Portland, Oregon, and is based on proprietary data. It combines six urban form variables into a score ranging from 20 to 100. The measure introduces several methodological refinements which have not been applied concurrently in previous efforts: a wide coverage of the different dimensions of the urban form, together with the use of a distance-based decay function and modelling-based weighing of the variables.This measure is applied to the GMA using local data in order to evaluate the feasibility of its transfer (the possibility of locally replicating the measure). It is then included in a series of mode choice models to assess its transferability (the capacity of the measure to describe walkability and predict mode choice in another urban area). The models, segmented by trip distance or trip purpose, are estimated and validated against observed trip data from the 2013 Origin-Destination survey.Significant positive correlation is found between the PIE and the choice of walking for short trips, for all purposes as well as for four specific trip purposes. The inclusion of the PIE also improves the accuracy of the modelling process as well as the prediction of the choice of walking for short trips. The PIE can therefore be used in the GMA, and potentially in other metropolitan areas, to improve the modelling of travel behavior for short trips.     

基于场变量的公路边坡稳定分析

利用 ABAQUS 中场变量对时间增量步控制的优势,提出了一种公路边坡稳定性分析新方法-基于场变量的强度折减法。对该方法应用于公路边坡稳定性分析的可行性进行验证,并与极限平衡法以及二分法计算得出的最小安全系数进行比较,分析其相对误差。结果表明：该方法用于公路边坡稳定性分析是有效、可靠的,提高了计算效率,对于公路工程边坡稳定性分析具有重要意义。     

一种短波非正交跳频网台信号分选方法研究

分析用于跳频网台信号分选的特征参数，提出一种基于特征指纹提取的时间相关算法进行短波非正交跳频网台信号分选，实验结果表明，在适当的信噪比条件下，该算法能够有效地完成二部非正交跳频网台信号的分选。     

任意随机变量序列关于广义随机选择系统的若干极限性质

采用鞅方法研究了对任意随机变量序列关于广义随机选择普遍成立的一类强极限定理,并作为推论得到了m阶马氏过程,鞅序列,鞅差序列,独立随机变量序列的一类强极限定理.把赌博系统的随机变换概念推广到任意随机变量序列,得到了任意随机变量序列随机选择与公平比的若干极限定理.     

基于ZMNL的相关复合K分布雷达海杂波仿真

相关K分布是一种适于描述雷达海杂波的非高斯分布模型。快速、准确地模拟雷达海杂波，对雷达最优信号处理器的设计及雷达系统的模拟是十分重要的。讨论了相关K分布海杂波的建模与仿真，在K分布的自相关函数与高斯分布的自相关函数之间的非线性关系的基础上，利用修正的零记忆非线性变换（ZMNL），仿真产生了相关复合K分布雷达海杂波。仿真实验结果表明，这种方法是准确、有效、可行的。     

阵元位置误差对MMUSIC算法测向性能的影响与分析

首先对MMUSIC算法进行了分析和仿真.然后重点讨论了阵元位置误差对MMUSIC算法测向性能的影响,并以均匀直线阵为例进行了仿真实验.从理论推导和仿真结果可以看出,天线阵阵元位置误差严重影响着MMUSIC算法测向性能,得出了有用结论.     

Accounting for stochastic variables in discrete choice models

The estimation of discrete choice models requires measuring the attributes describing the alternatives within each individual’s choice set. Even though some attributes are intrinsically stochastic (e.g. travel times) or are subject to non-negligible measurement errors (e.g. waiting times), they are usually assumed fixed and deterministic. Indeed, even an accurate measurement can be biased as it might differ from the original (experienced) value perceived by the individual.Experimental evidence suggests that discrepancies between the values measured by the modeller and experienced by the individuals can lead to incorrect parameter estimates. On the other hand, there is an important trade-off between data quality and collection costs. This paper explores the inclusion of stochastic variables in discrete choice models through an econometric analysis that allows identifying the most suitable specifications. Various model specifications were experimentally tested using synthetic data; comparisons included tests for unbiased parameter estimation and computation of marginal rates of substitution. Model specifications were also tested using a real case databank featuring two travel time measurements, associated with different levels of accuracy.Results show that in most cases an error components model can effectively deal with stochastic variables. A random coefficients model can only effectively deal with stochastic variables when their randomness is directly proportional to the value of the attribute. Another interesting result is the presence of confounding effects that are very difficult, if not impossible, to isolate when more flexible models are used to capture stochastic variations. Due the presence of confounding effects when estimating flexible models, the estimated parameters should be carefully analysed to avoid misinterpretations. Also, as in previous misspecification tests reported in the literature, the Multinomial Logit model proves to be quite robust for estimating marginal rates of substitution, especially when models are estimated with large samples.     

计算机辅助船舶技术经济论证

本文介绍了 Apollo CAD 工作站上开发的船舶技术经济论证系统,并叙述了船舶技术经济论证的计算方法,文中还详细讨论了在应用计算机条件下本系统所具有的一些特色,如指标与变量关系曲面的构成,多目标优选方案等,最后阐述了本系统的总体结构及运行环境.