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.     

Spatial pattern of the global shipping network and its hub-and-spoke system

Port system is a research focus of transport geography, and most studies believe carriers are important factors in the development and concentration of the port system. Since the 1990s, carriers have played an important role in organizing the global shipping network and reorganizing the port system. But there isn’t a perfect method to evaluate carriers’ influence and the roles of each port in the maritime shipping networks. In this paper, we use the monthly schedule table of international carriers to describe and model the spatial pattern of the global shipping network and identify its hub-and-spoke system. The result shows that a hierarchical structure exists in the global shipping network. The North Hemisphere, especially the East Asia and the Southeast Asia, is a dominant region of the worldwide shipping network. East Asia, Southeast Asia, Northeast Europe, and East coast of the USA are the concentration regions of worldwide shipping lines. The ports of Hong Kong, Singapore, Shenzhen, Shanghai, and Kaohsiung etc have advanced capacity for maritime shipping and high potentials for being hub ports in the global shipping network. Today, the worldwide shipping network is transforming from the multi-port calling system to 44 regional hub-and-spoke systems. Meanwhile, the sub-networks with hub ports of Antwerp, Singapore, and Hong Kong have become the most important ones and dominate the whole global shipping network.     

半潜式钻井平台总装建造技术研究

以中集来福士海洋工程有限公司某半潜钻井平台总装建造过程为研究对象,提出了一种新型的半潜平台总装建造方案,详细阐述了海洋工程装备总装建造几个核心技术,归纳总结出半潜式钻井平台总装建造实施方案,最终形成了一套完整的半潜钻井平台总装建造流程。     

基于均衡载客量的公交时刻表优化方法研究

本文首先介绍发车频率及发车间隔的确定方法,然后结合各公交站点在各时间段的平均观测客流量数据．以均衡载客量为原则．讨论了两种基于均衡载客量的公交时刻表编制方法：均衡最大载客断面载客量的时刻表编制方法与均衡单个车辆最大载客量的时刻表编制方法,并阐述了两种时刻表的编制流程。     

A joint optimization model for liner container cargo assignment problem using state-augmented shipping network framework

This paper proposes a state-augmented shipping (SAS) network framework to integrate various activities in liner container shipping chain, including container loading/unloading, transshipment, dwelling at visited ports, in-transit waiting and in-sea transport process. Based on the SAS network framework, we develop a chance-constrained optimization model for a joint cargo assignment problem. The model attempts to maximize the carrier’s profit by simultaneously determining optimal ship fleet capacity setting, ship route schedules and cargo allocation scheme. With a few disparities from previous studies, we take into account two differentiated container demands: deterministic contracted basis demand received from large manufacturers and uncertain spot demand collected from the spot market. The economies of scale of ship size are incorporated to examine the scaling effect of ship capacity setting in the cargo assignment problem. Meanwhile, the schedule coordination strategy is introduced to measure the in-transit waiting time and resultant storage cost. Through two numerical studies, it is demonstrated that the proposed chance-constrained joint optimization model can characterize the impact of carrier’s risk preference on decisions of the container cargo assignment. Moreover, considering the scaling effect of large ships can alleviate the concern of cargo overload rejection and consequently help carriers make more promising ship deployment schemes.     

On the cost of misperceived travel time variability

Because individuals may misperceive travel time distributions, using the implied reduced form of the scheduling model might fall short of capturing all costs of travel time variability. We reformulate a general scheduling model employing rank-dependent utility theory and derive two special cases as econometric specifications to study these uncaptured costs. It is found that reduced-form expected cost functions still have a mean–variance form when misperception is considered, but the value of travel time variability is higher. We estimate these two models with stated-preference data and calculate the empirical cost of misperception. We find that: (i) travelers are mostly pessimistic and thus tend to choose departure times too early to achieve a minimum cost, (ii) scheduling preferences elicited using a stated-choice method can be relatively biased if probability weighting is not considered, and (iii) the extra cost of misperceiving the travel time distribution might be nontrivial when time is valued differently over the time of day and is substantial for some people.     

多级挣值法在船厂作业进度管控中的应用

针对挣值法在船厂作业进度管控时偏重于单项目整体进度管控而忽略项目内部任务包逻辑关系的不足,本文在挣值法的理论基础上,结合船厂作业基本单元-任务包,提出了基于任务包的多级挣值法,并以船厂某总段建造为例对该方法应用效果进行分析。通过研究表明,基于任务包的多级挣值法弥补了挣值法的不足,实现了对船厂作业进度有效的管控。     

Optimality of environmental policies in air transport markets and changes in the schedule delay: A theoretical approach

Air transport provides essential services in modern economies, though it produces significant negative external effects on the environment. Air quality, greenhouse gas emissions and noise are the main issues. The current environmental regulatory practice in air transport usually devises policy interventions for each externality in isolation disregarding their impact on the schedule delay, which in turn affects the consumers’ generalized price and social welfare. In this paper we develop a theoretical model that shows that such an approach is inadequate, and may lead to the choice of wrong environmental policies.     

Coastal Management Using Public Judgments,Importance Scales,and Predetermined Schedule

A predetermined schedule of sanctions and regulations that reflect both scientific knowledge of resources and the preference and judgments of resource users in the community may provide a useful guide for management decisions involving complex coastal resource systems. Such a schedule can be implemented by constructing scales reflecting public judgments of the relative importance of adverse impacts on resources, or of activities causing such impacts. The importance scales can then be used to assess existing regulations and current management priorities and to serve as a guide for revisions and changes to current practice, for the design of new policy, for rationalizing regulatory controls, and for determining damage awards and other deterrence sanctions. The resulting evolution of a schedule can improve the consistency of resource use with community preferences by, for example, prescribing more severe restrictions on what are widely agreed to be more serious harms and lesser controls on less important ones. The application of this approach is demonstrated using Ban Don Bay, Thailand.