Integrating capacity analysis with high-speed railway timetabling: A minimum cycle time calculation model with flexible overtaking constraints and intelligent enumeration

Compared with most optimization methods for capacity evaluation, integrating capacity analysis with timetabling can reveal the types of train line plans and operating rules that have a positive influence on improving capacity utilization as well as yielding more accurate analyses. For most capacity analyses and cyclic timetabling methods, the cycle time is a constant (e.g., one or two hours). In this paper, we propose a minimum cycle time calculation (MCTC) model based on the periodic event scheduling problem (PESP) for a given train line plan, which is promising for macroscopic train timetabling and capacity analysis. In accordance with train operating rules, a non-collision constraint and a series of flexible overtaking constraints (FOCs) are constructed based on variations of the original binary variables in the PESP. Because of the complexity of the PESP, an iterative approximation (IA) method for integration with the CPLEX solver is proposed. Finally, two hypothetical cases are considered to analyze railway capacity, and several influencing factors are studied, including train regularity, train speed, line plan specifications (train stops), overtaking and train heterogeneity. The MCTC model and IA method are used to test a real-world case involving the timetable of the Beijing–Shanghai high-speed railway in China.     

Evaluating sustainability of supply chains by two-stage range directional measure in the presence of negative data

Assessing sustainability of supply chains is a critical and increasingly complex problem. In recent years sustainability has received more attention in supply chain management (SCM) literature with triple bottom lines including social, environmental, and economic factors. Conventional data envelopment analysis (DEA) models consider decision making units (DMUs) as black boxes that consume a set of inputs to produce a set of outputs and do not take into consideration internal interactions of DMUs. Two-stage DEA models deal with such DMUs. However, existing two-stage DEA models are applicable only in technologies characterized by positive inputs/outputs. This paper aims to build and present a new two-stage DEA model considering negative input-intermediate-output data. Some numerical examples along with some theorems and properties are given to show capability of proposed method. The proposed ideas are used in a case study where 29 Iranian supply chains producing equipment of expendable medical devices are evaluated in terms of sustainability.     

A carbon footprint-based closed-loop supply chain model under uncertainty with risk analysis: A case study

The management of products’ end-of-life and the recovery of used products has gained significant importance in recent years. In this paper, we address the carbon footprint-based problem that arises in a closed-loop supply chain where returned products are collected from customers. These returned products can either be disposed of or be remanufactured to be resold as new ones. Given this environment, an optimization model for a closed-loop supply chain (CLSC) in which carbon emission is expressed in terms of environmental constraints, i.e., carbon emission constraints, is developed. These constraints aim to limit the carbon emission per unit of product supplied with different transportation modes. Here, we design a closed-loop network where capacity limits, single-item management and uncertainty on product demands and returns are considered. First, fuzzy mathematical programming is introduced for uncertain modeling. Then, the statistical approach to the possibility to synthesize fuzzy information is utilized. Therefore, using a defined possibilistic mean and variance, we transform the proposed fuzzy mathematical model into a crisp form to facilitate efficient computation and analysis. Finally, the risk caused by violating the estimated resource constraints is analyzed so that decision makers (DMs) can trade off between the expected cost savings and the expected risk. We utilize data from a company located in Iran.     

The vulnerability of the environment to spills of dangerous substances on highways: A diagnosis based on multi criteria modeling

Highways and freeways are the main infrastructure channel used to transport cargo in Brazil. This cargo often includes dangerous chemical products which can, in the event of an accident, negatively impact the environment. The development and implementation of tools for the rapid diagnosis of environmental vulnerability in the transportation of dangerous goods has been studied. However, for highways and freeways there is a lack of studies based on environmental attributes, and not just based on statistical data which demands a specific period for collection and analysis and only after that the implementation of preventive measures. Thus, evaluation grounded on multiple criteria embedded in Geographic Information System (GIS) has significant potential for the practical implementation of risk management of road transportation of dangerous goods. This study has determined the environmental vulnerability of route BR 050, specifically the segment between the cities of Uberlândia and Uberaba in the state of Minas Gerais, where multi criteria analysis has been efficient in determining the most vulnerable areas. The main attributes analyzed were the drainage density, soil type and geology, determining that in case of an accident with dangerous substances the regional environment would be immediately affected, and so endorsing the use of this tool in many segments involved in environmental management of highway enterprises.     

Urban single-lane roundabouts: A new analytical approach using multi-criteria and simultaneous multi-objective optimization of geometry design,efficiency and safety

Building safe and effective roundabouts requires optimizing traffic (operational) efficiency (TE) and traffic safety (TS) while taking into account geometric factors, traffic characteristics and local constraints. Most existing simulation-based optimization models do not simultaneously optimize all these factors. To capture the relationship among geometry, efficiency and safety, we put forward a model formulation in this paper. We present a new multi-criteria and simultaneous multi-objective optimization (MOO) model approach to optimize geometry, TE and TS of urban unsignalized single-lane roundabouts. To the best of our knowledge, this is the first model that uses the multi-criteria decision-making method known as analytic hierarchy process to evaluate and rank traffic parameters and geometric elements of urban single-lane roundabouts. The model was built based on comprehensive review of the research literature and existing roundabout simulation software, a field survey of 61 civil and traffic expert engineers in Croatia, and field studies of roundabouts in the Croatian capital city of Zagreb. We started from the basis of Kimber’s capacity model, HCM2010 serviceability model, and Maycock and Hall's accident prediction model, which we extended by adding sensitivity analysis and powerful MOO procedures of the bounded objective function method and interactive optimization. Preliminary validation of the model was achieved by identifying the optimal and most robust of three geometric alternatives (V.1-V.3) for an unsignalized single-lane roundabout in Zagreb, Croatia. The geometric parameters in variant V.1 had significantly higher values than in the existing design V.0, while approaches 1 and 3 in variant V.2 were enlarged as much as possible within allowed spatial limits and Croatian guidelines, reflecting their higher traffic demand. Sensitivity analysis indicated that variant V.2 showed the overall highest TE and TS across the entire range of traffic flow demand and pedestrian crossing flow demand at approaches. At the same time, the number of predicted traffic accidents was similar for all three variants, although it was lowest overall for V.2. The similarity in predicted accident frequency for the three variants suggests that V.2 provides the greatest safety within the predefined constraints and parameter ranges explored in our study. These preliminary results suggest that the proposed model can optimize geometry, TE and TS of urban single-lane roundabouts.     

高速公路山岭隧道设计阶段安全风险评估

通过定性分析与定量分析相结合的方法,利用专家分析法和层次分析法研究各风险控制因素与权值.从技术角度考虑设计方案中各种不确定因素对后续施工及运营造成的不利影响,并得出相关结论,对于指导实际工作有一定的意义.     

Investigating Causal Pathways Linking Site-Level Characteristics,Compliance, and Ecological Performance in Caribbean MPAs

A rapidly growing body of empirical evidence has linked improved ecological performance of social–ecological systems (SES) with better compliance with rules governing human activities. Researchers have proposed several key factors that motivate an individual to comply with resource use rules, including deterrence, social pressures, moral inclinations, and perceived legitimacy of rules and responsible authorities. Much of the research on compliance proposes causal mechanisms at the individual human level, but few studies test causal paths with empirical data particularly at the site level. This study tested a proposed pathway for explaining overall compliance rates and ecological performance in SES using data from structured surveys of community members, key informant interviews, policy documents, and coral reef surveys at marine protected areas (MPAs) and their associated human communities in the wider Caribbean. Findings indicate that compliance and other active MPA management interventions positively affect ecological performance, and site-level contextual factors (level of community development and being part of a political network) positively influence significant predictors of overall compliance rates, which include active MPA management and enforced punishments.     

基于物元分析法的公路桥梁损伤等级评定研究

在构建桥梁损伤等级评定指标体系的基础上，采用 AHP确定了各指标的权重，运用物元分析的方法建立了桥梁损伤等级评定的数学模型，并利用模型评定结果，得到了某桥梁的损伤等级。     

山区漫水桥梁水毁调查分析及重建设计

重点阐述在涞水县7.21灾后公路恢复重建中，对桥梁水毁状况的调查分析以及工程重建设计要点，可为相关工作提供借鉴。     

Plate scanning tools to obtain travel times in traffic networks

The management of vehicle travel times has been shown to be fundamental to traffic network analysis. To collect travel time measurement, some methods focus solely on isolated links or highway segments, and where two measurement points, at the beginning and at the end of a section, are deemed sufficient to evaluate users' travel time. However, in many cases, transport studies involve networks in which the problem is more complex. This article takes advantage of the plate scanning technique to propose an algorithm that minimizes the required number of registering devices and their location in order to identify vehicles candidates to compute the travel times of a given set of routes (or subroutes). The merits of the proposed method are explained using simple examples and are illustrated by its application to the real network of Ciudad Real.