A stochastic analysis of highway capacity: Empirical evidence and implications

This paper presents a stochastic characterization of highway capacity and explores its implications on ramp metering control at the corridor level. The stochastic variation of highway capacity is captured through a Space–Time Autoregressive Integrated Moving Average (STARIMA) model. It is identified following a Seasonal STARIMA model (0, 0, 2₃) × (0, 1, 0)₂, which indicates that the capacities of adjacent locations are spatially–temporally correlated. Hourly capacity patterns further verify the stochastic nature of highway capacity. The goal of this paper is to study (1) how to take advantage of the extra information, such as capacity variation, and (2) what benefits can be gained from stochastic capacity modeling. The implication of stochastic capacity is investigated through a ramp metering case study. A mean–standard deviation formulation of capacity is proposed to achieve the trade-off between traffic operation efficiency and robustness. Following that, a modified stochastic capacity-constraint ZONE ramp metering scheme embedded cell transmission model algorithm is introduced. The numerical experiment suggests that considering capacity variation information would alleviate the spillback effect and improve throughput. Monte Carlo simulation further supports this argument. This study helps verify and characterize the stochastic nature of capacity, validates the benefits of using capacity variation information, and thus enhances the necessity of implementing stochastic capacity in traffic operation.     

Location privacy preferences: A survey-based analysis of consumer awareness,trade-off and decision-making

With the advent and rapid dissemination of location-sensing information technology, the issue of location information privacy is receiving growing attention. Perhaps of greatest concern is ensuring that potential users of mobile Information and Communications Technologies (e.g., Location-Based Services and Intelligent Transportation Systems) are comfortable with the levels of privacy protection afforded them, as well as with the benefits they will receive in return for providing private location information. This paper explores the concepts of privacy risks, benefits, willingness to trade, and compensation in relationship to mobile and locational technologies using a stated preference survey to ascertain areas of interest in determining the trade-offs that consumers will be willing to make in return for mobility enhancements. Analysis of the survey leads to findings that while respondents believe that sharing data in the mobile environment may pose privacy risks, they do not generally take steps necessary to address these risks; that privacy preferences are impacted by a range of factors, including both personal and contextual considerations (such as factors arising from their specific situation at the time of information seeking); and that willingness to trade private location data is dependent upon a number of factors related to context, personal characteristics, expected benefits and degree of trust in the collecting organization.     

导弹发射装置可靠性指标体系研究

针对导弹发射装置研制的特点,研究了发射装置基本可靠性指标、任务可靠性指标、维修性指标、贮存性指标及这些指标的相关性,提出了开展发射装置可靠性指标论证的原则、步骤及方法.应用综合权衡法,考虑研制费用、保障费用与全寿命周期费用的因素,给出了发射装置各研制阶段的可靠性指标体系.     

基于使用可用度的舰船电子信息系统R MS 参数权衡方法*

舰船电子信息系统是舰船武器装备重要组成,针对研制阶段其可靠性、维修性、保障性参数（RM S参数）的综合权衡问题,以使用可用度为约束,以实现寿命周期费用最低为目标,提出了基于使用可用度的RM S参数权衡方法,并给出了权衡方法中,基于RM S参数的使用可用度及寿命周期费用的计算模型。     

工程项目管理中工期-费用-质量的权衡分析

根据集成管理的思想,通过质量衡量体系得到质量与工期和费用的敏感程度,基于工期和费用的优化,对工期、费用和质量做出综合的权衡分析。     

多属性权衡理论在舰船优化设计中的应用研究

探讨了多属性权衡理论在舰船优化设计中的应用方式，并以舰船推进装置和电站方案的权衡分析为例，在基于舰船设计综合模型的基础上，得出了衡量方案优劣的属性值。采用权衡分析的方式，为舰船方案的优化提供了一种实用的手段。     

Research on the fully fuzzy time-cost trade-off based on genetic algorithms

It is very difficult to estimate exact values of time and cost of an activity in project scheduling process because many uncertain factors, such as weather, productivity level, human factors etc. , dynamically affect them during project implementation process. A GAs-based fully fuzzy optimal time-cost trade-off model is presented based on fuzzy sets and genetic algorithms （GAs）. In tihs model all parameters and variables are characteristics by fuzzy numbers. And then GAs is adopted to search for the optimal solution to this model. The method solves the time-cost trade-off problems under an uncertain environment and is proved practicable through a giving example in ship building scheduling.