Measuring carbon emissions is an essential step in taking required action to fight global warming. This research presents a computational method for measuring transport related carbon emissions in a healthcare supply network. The network configuration significantly impacts carbon emissions. First, a multi-objective mathematical programing model is developed for designing a healthcare supply network in the form of a two-graph location routing problem under demand and fuel consumption uncertainty. Objective functions are minimizing total cost and minimizing total fuel consumption. In the presented model, the demand of each customer must be completely satisfied in each time period, and backlog is not permitted. The number and capacity of vehicles are determined, and vehicles are heterogeneous. Furthermore, fuel consumption depends on traveling distance, vehicle and road conditions, and the load of a vehicle. The centroid method is applied to face demand uncertainty. Next, a multi-objective non-dominated ranked genetic algorithm (M-NRGA) is proposed to solve the model. Then, a Monte Carlo based approach is presented for measuring 
transport-related carbon emissions based on fuel consumption in supply network. Finally, the proposed approach is applied to the case of a healthcare supply network in the Fars province in Iran. The obtained results illustrate that the proposed approach is a practical tool in designing healthcare supply networks and measuring transport-related carbon emissions in the network.

Low-carbon transport is a priority in addressing climate change. Transport is still almost totally dependent on fossil fuels (96%) and accounts for almost 60% of global oil use. Sustainable transport systems, both passenger and freight, should be economically and technically feasible, but also low-carbon and environmentally friendly. The calculation of greenhouse gas emissions in transport projects is becoming a primary target of transport companies as a part of an endeavor for low-carbon strategies to reduce the energy demand and environmental impact. This paper investigates the CO₂ impact of construction and operation of the main highway and railway line infrastructure in Greece, which connects Athens and Thessaloniki, the capital and the second biggest city in Greece respectively and provides a comparative analysis in roadway and railway transport.

Train timetable is the key document to regulate railway traffic through sequencing train movements to keep the appropriate order. Timetable stability and on-schedule rate are closely related. Delays caused by disturbances in train operations can be absorbed by a high quality timetable with high stability, and the on-schedule rate then can be assured. This paper improves the stability of timetables of several connected railway sections to assure the on-schedule rate with a simulation method. Firstly, we build a macroscopic network model of train operation in a railway network using the Petri net theory. Then we design the train tracking subnet model, the station subnet model and arrival-departure track subnet model. At last we propose a computing case, simulating the train operation process based on the presented models, and the simulation results prove the feasibility and availability of the models. The approach presented in this paper can offer valuable decision-support information for railway operators preparing train timetables.

In many countries, bus operators are private companies whose service has been leased by government agencies. These agencies develop service compliance indices or measures to keep track of factors such as passenger satisfaction, frequency, and regularity but do not necessarily include the objectives of the operators in the assessment. In this paper, we used slack-based measure data envelopment analysis (SBM) to investigate whether it is possible for a bus operator to be efficient (from a private perspective) and match required standards of frequency and regularity. In doing so, data collected from two major bus operators in Santiago, Chile has been used comprising 99 services. The results show that when private objectives, namely revenues, are included in the analysis, bus operators do not necessarily seek to improve the regularity of their service. Moreover, it was found that some bus services are on the efficient frontier while keeping low performance measure standards. Using the shadow prices of the models, it was also found that improving the performance measures will be hard for many bus services unless there is a significant change in factors that are not under control of the operators (i.e., number of stops, length of the route, etc.). This shows the difficulty of correctly aligning the private objectives of operators with agencies’ objectives.

Reasonable selection of passenger flow routes considering
different transportation organization modes can meet
the demands of adapting to large-scale high-speed railway
networks and improving network efficiency. Passenger flow
routing models are developed to find and optimize a set
of passenger flow routes for a high-speed railway network considering different transportation organization modes. In this paper, we presented a new approach minimizing the operating costs, including traveling cost, cost of travel time differences between different lines, and penalties for the inter-line. The network was reconstructed to solve the directed graph with four nodes (node-in-up, node-in-down, nodes-outup, and nodes-out-down) indicating one station. To tackle our problem, we presented an integer non-linear programming model, and direct passenger demand was guaranteed owing to volume constraints. Binary variables were introduced to simplify the model, and the algorithm process was optimized. We suggested a global optimal algorithm by Lingo 11.0. Finally, the model was applied to a sub-network of the Northeast China railway system. Passenger flow routes were optimized and the transportation organization mode was discussed based on passenger volume, traveling distance, and infrastructure.

A driver’s reaction time encountering hazards on roads involves different sections, and each section must occur at the right time to prevent a crash. An appropriate reaction starts with hazard detection. A hazard can be detected on time if it is completely visible to the driver. It is assumed in this paper that hazard properties such as size and color, the contrast between the environment and a hazard, whether the hazard is moving or fixed, and the presence of a warning are effective in improving driver hazard detection. A driving simulator and different scenarios on a two-lane rural road are used for assessing novice and experienced drivers’ hazard detection, and a Sugeno fuzzy model is used to analyze the data. The results show that the hazard detection ability of novice and experienced drivers decreases by 35% and 64%, respectively, during nighttime compared to daytime. Also, moving hazards increase hazard detection ability by 9% and 180% for experienced and novice drivers, respectively, compared to fixed hazards. Moreover, increasing size, contrast, and color difference affect hazard detection under nonlinear functions. The results could be helpful in safety improvement solution prioritization and in preventing vehicle-pedestrian, vehicle-animal, and vehicle-object crashes, especially for novice drivers.

For a long time, many researchers have investigated the continuous network design problem (CNDP) to distribute equitably additional capacity between selected links in a road network, to overcome traffic congestion in urban roads. In addition, CNDP plays a critical role for local authorities in tackling traffic congestion with a limited budget. Due to the mutual interaction between road users and local authorities, CNDP is usually solved using the bilevel modeling technique. The upper level seeks to find the optimal capacity enhancements of selected links, while the lower level is used to solve the traffic assignment problem. In this study, we introduced the enhanced differential evolution algorithm based on multiple improvement strategies (EDEMIS) for solving CNDP. We applied EDEMIS first to a hypothetical network to show its ability in finding the global optimum solution, at least in a small network. Then, we used a 16-link network to reveal the capability of EDEMIS especially in the case of high demand. Finally, we used the Sioux Falls city network to evaluate the performance of EDEMIS according to other solution methods on a medium-sized road network. The results showed that EDEMIS produces better solutions than other considered algorithms, encouraging transportation planners to use it in large-scale road networks.

The growth in air traffic in recent decades in Europe has consequently caused aircraft delays due to insufficient capacities of airspace and airports. Primary and reactionary delays at certain European and Croatian coastal airports in 2014 are analyzed in the paper according to CODA methodology and classified according to main flight delays causes. The largest share of delay minutes at the Croatian coastal airports (75%) are related to reactionary delays, ranging from around 20% to 60% of total delay at the most congested European airports. Special emphasis is given to the analyses of rotational reactionary delay, and the results indicate that the share of reactionary delay in total delay at the Split airport is significantly higher compared to selected European airports, which may be explained by delays propagated from air traffic network and limited airport capacity. The total recorded delay at Croatian coastal airports is minor compared to total recorded delay in the European air traffic system, but delay patterns are quite similar, especially during peak summer months.

Queue discharge flow is the most frequently observed phenomenon on urban motorways when demand exceeds capacity. Once a queue is formed, congestion arises, and the number of vehicles that can pass from downstream reduces. This reduction phenomenon is defined as the capacity drop and calculated by taking the difference between capacity and discharge flow at a road section. Obviously, this capacity drop exists after an onset of congestion and may increase in relation to weather conditions, such as rain, snow, or fog, which cause longer queues and delays. In this paper, the effect of rain on discharge flows is investigated and compared with sunny days on Istanbul urban motorways. Besides, rain precipitation during congestion is considered and related to discharge flow. Four different motorway sections were analyzed, and up to 37% discharge flow reduction was determined between sunny and rainy conditions. Motorway sections with higher free flow speed (FFS) were found to be more affected by rain, and discharge flow reduction was bigger compared to the section with the lowest FFS. For 1 mm/m²/h of precipitation, the discharge flow is estimated as 1,719 pcu/h/lane when FFS is 84 km/h, and as 1,560 pcu/h/lane if FFS is 104 km/h.

Designing tariff systems in public passenger transport is a complex issue of optimization by means of satisfying the wants and needs of all the engaged parties. An integrated passenger transport system (IPTS) stands for the concept of organization and management of public passenger transport based on a uniform tariff system. The issue of transport disadvantage of certain peri-urban and rural areas is the result of poorly organized transport systems. Social and spatial isolation in the framework of mobility is partly the fault of the way in which tariff systems have been designed with no regard to the social factors of the engaged parties for which such systems are designed – its users. Special emphasis in the research of tariff systems is placed on resolving issues of designing tariff zones, maximizing social welfare, transport equity, and transport disadvantage. An outline of the existing research and a review of literature concerning tariffs in integrated passenger transport systems is given, and proposals are put forward for future research due to the need for designing socially beneficial tariff systems, which would eliminate social exclusion, i.e., the transport disadvantage of individuals or parts of society.