Optimizing train frequencies and train routing with simultaneous passenger assignment in high-speed railway network

This study investigates an integrated train stop planning and timetabling problem considering the uncertainty of passenger demand in a railway network. With the scenario-based representation of demand distribution, an integer linear programming (ILP) model is formulated to simultaneously optimise the train timetable and stop plan, in which the time-space network representation method is adopted to characterise the movements of trains and passengers. The objective is to jointly optimise the total travel time of trains and passengers, and the expected number of unsatisfied or over-satisfied passengers over all demand scenarios. By analyzing the characteristics of the model, we decompose it into two subproblems based on trains (timetabling) and passengers (assignment), respectively. Then, an iterative algorithm based on variable neighbourhood search (VNS) is designed to solve the two subproblems iteratively. Additionally, a series of numerical experiments based on the real-world instance in a high-speed railway (HSR) network are implemented to verify the effectiveness of the proposed stochastic programming (SP) model and the iterative algorithm. The results demonstrate that (i) the proposed SP model is easy to implement in practice, and (ii) the developed iterative algorithm exhibits much higher computational efficiency than the optimisation solver.

Optimization of Urban Single-line Metro Timetable for Total Passenger Travel Time under Dynamic Passenger Demand

In high-speed railway (HSR) networks, wireless link connection is fragile because of fast train speed and severe fading environment. Link lifetime is an important metric for many safety and non-safety applications that require a radio connection to be maintained for an entire communication session. An analytical modeling structure is proposed for estimating the probability density function (PDF) of link lifetime under auto-correlated shadow fading environment in HSR networks. A discrete-time Markov chain (DTMC) based model is proposed to model both pathloss and auto-correlated shadowing components into a transition process. Based on the proposed DTMC model, the PDF of the link lifetime between a communication pair can then be more accurately derived. Performance of the model is verified by a measurement campaign conducted along a part of the Zhengzhou-Xi'an HSR networks in China.

Network periodic train timetabling with integrated stop planning and passenger routing: A periodic time–space network construct and ADMM algorithm

Vulnerability analysis of the Chinese coupled aviation and high-speed railway network

In the transportation organization optimization of high-speed railway (HSR), optimizations such as line planning, ticket pricing, and seat allocation are generally studied separately. However, in reality, when passengers choose trains, they need to consider multiple factors such as train routes, stop plans, seat prices, seat availability, and departure times. Therefore, there is an urgent need for an integrated optimization method to simultaneously make decisions regarding these multiple factors. This study constructs a nonlinear optimization model of line planning integrating differentiated pricing and seat allocation decisions for HSR under elastic demand. To efficiently solve the model, an improved heuristic algorithm based on the simulated annealing framework combined with a linear passenger flow allocation method is proposed. Finally, case analysis proves that the improved algorithm can effectively solve the model under the input conditions of an actual Y-shaped HSR network composed of 13 stations, with a potential for a 106.54% improvement from the initial solution to the final solution. The uniqueness of our study lies in the joint optimization of three critical HSR operations, which has not been comprehensively explored in prior studies and is of great significance for improving the level of HSR train operations and passenger services.

In response to urban rail transit capacity shortage, a capacity adaption optimization model for the new mixed train operation mode is proposed in the supernormal operation of urban rail transit networks. First, the characteristics of express-local train and long-short route slow train are analyzed to obtain the main influencing factors of capacity adaption. Moreover, various train types are simultaneously classified and recombined in the adaption train operation mode to maximize transportation capacity for passengers. A nonlinear mixed-integer programming model is established to maximize the total number of trains, improving train load rate and reducing the total passenger travel time. In addition, the actual case of Beijing Metro Line 1 is solved to demonstrate the feasibility and effectiveness of the proposed model. The optimal passenger travel time-saving rates of the morning and evening peak hours are 12.1% and 11.5%, respectively. The optimal utilization rates of capacity in the morning and evening peak hours are 79.5% and 84.5%, respectively. Meanwhile, the optimal load factor within the range of 0.7–0.9 would benefit the utilization of train resources and the passengers’ service level. The optimized results show that the proposed capacity adaption optimization model benefits for high service level and practical significance and rationality for operators.

The suburban railway adopts the mode of combined operation of express and local trains, which can solve the problems of uneven temporal and spatial distribution of passenger flow, meet the diversified needs of passengers, improve transportation efficiency and reduce operating costs. By analyzing and summarizing the passenger flow characteristics and transportation demand of suburban railway, aiming at minimizing the total travel time of passengers and enterprise operating cost, a nonlinear optimization model of suburban railway operation scheme is established. Considering the influence factors such as minimum tracking interval constraint and cross-sectional passenger flow constraint and completes the solution of the model by Lingo. The optimization results after running express and local trains show that the total travel time of passengers is reduced by about 97 minutes, and the enterprise operating cost is reduced by 30%, which proves that the proposed model is efficient and feasible.

In this work, a new multi-objective mixed integer nonlinear programming (MINLP) model based on Pinch Technology principles is presented. The proposed framework is able to simultaneously maximize the heat recovery, minimize the total heat exchange surface while guaranteeing the heat transfer feasibility. The formulation adopted for the heat integration problem significantly reduces the number of binary variables when dealing with variable temperatures and flowrates, thus enhancing the solution efficiency. The model is then augmented with the introduction of a novel approach for the total area estimation not requiring heavy disjunctions nor complex tailor-made algorithms. A study on the optimization of an air separation unit (ASU) is finally performed to show the potential and effectiveness of the proposed framework.

The article deals with a comprehensive historical and analytical study of the formation and evolution of high-speed railway transport as one of the key technological and sociocultural transformations of modern society. The aim of the article is to reveal historical patterns of formation, technical evolution and socio-cultural significance of high-speed railway transport in a global context. The authors aim to show how the desire for speed became not only an engineering challenge, but also a driver of economic, urban and civilisational modernisation. An interdisciplinary approach combining historical-technical, comparative and socio-economic analysi has been used. Such a combination is justified by the essence of high-speed railways. They are not just a transport technology, but a phenomenon that combines material engineering, state policy, the culture of speed, and human perceptions of space and time. For this reason, the logic of the study is not limited to a list of technical facts, but aims to show how an engineering idea gradually became a social reality. The source base includes peer-reviewed scientific publications, technical reports from railway companies, documents from international organisations, and contemporary research on the history of transport and engineering. The technical background of high-speed rail transport has been analysed since 19th-century railways to post-war projects of the mid-20th century, including Japan’s Shinkansen system, France’s TGV and Germany’s ICE, as well as the subsequent development of a global high-speed railway network in China, Europe and other countries. The article combines technical, engineering, socio-economic, and cultural-civilisational approaches. It is shown that high-speed railway is not only an infrastructural phenomenon but also a social one, shaping mobility, urbanisation, regional integration, and environmental sustainability. The latest innovations of the 21st century: magnetic levitation, Hyperloop systems, and digitalisation, determining the transition to the era of energy-intelligent mobility have been considered separately. It has been concluded that the history of high-speed railway transport reflects the overall evolution of engineering thought, public policy and the culture of speed, which is transforming humanity's understanding of space, time and steady development.

Developing public transportation is an effective way to alleviate traffic congestion and reduce fossil fuel consumption. However, the result of ineffective public transport planning can be that some bus lines have long overlapping intervals, and share many common stops between them, which causes a significant waste of resources. The current bus scheduling method does not consider the imbalance of passenger flow between different stops or combine the overlapping interval with transit mixed scheduling, including all-stop and stop-skipping services. Therefore, based on the analysis of the characteristics of overlapping interval, this paper proposes a combined bus scheduling method, which includes both all-stop and stop-skipping bus services. The method is a deterministic method applied in the scheduling stage of transit planning. The method optimizes scheduling strategies by minimizing total passenger travel time, including the waiting time and the in-vehicle travel time, and the line frequency of each bus service is taken as the decision variable. Then a genetic algorithm is designed to find the optimal solution. The model is verified by two bus lines in Changchun city. The experimental results showed that the proposed model could reduce total passenger travel time by 7.71% compared with the existing scheduling method. The combined bus scheduling method can supplement the research on bus scheduling of overlapping routes and provide suggestions for operators.

A robust, tactic-based, real-time framework for public-transport transfer synchronization

"Medium and Long Term Railway Network Planning" describes the grand blueprint of "eight vertical and eight horizontal" high-speed railway network, marking that China has officially entered the heyday of high-speed railway construction. At present, China is in a leading position in the development of high-speed railway in the world. This research selects China’s high-speed railway transport network from 2014 to 2020 as the research object, high-speed railway stations as network nodes, the ratio of passenger flow to running time as the edge weight, and builds a weighted undirected network diagram. Gephi is used to visualize the high-speed railway transport network. Finally, the spatio-temporal variation rules of China’s high-speed railway transport network are explored from two aspects of nodes and the whole network. It is found that the difference of different node degrees will gradually change from large in the early stage to small in 2020. Small world features are becoming more and more prominent, and network performance is improving. China’s high-speed rail network was initially developed mainly in the economically developed central and eastern regions, but has gradually shifted to the western region since 2017. China’s high-speed rail transport network has shifted from economically developed, densely populated areas to underdeveloped, sparsely populated areas with transportation demands.

Bus stops are key links in the journeys of transit patrons with disabilities. Inaccessible bus stops prevent people with disabilities from using fixed-route bus services, thus limiting their mobility. The Americans with Disabilities Act (ADA) of 1990 prescribes the minimum requirements for bus stop accessibility by riders with disabilities. Due to limited budgets, transit agencies can only select a limited number of bus stop locations for ADA improvements annually. These locations should preferably be selected such that they maximize the overall benefits to patrons with disabilities. In addition, transit agencies may also choose to implement the universal design paradigm, which involves higher design standards than current ADA requirements and can provide amenities that are useful for all riders, like shelters and lighting. Many factors can affect the decision to improve a bus stop, including rider-based aspects like the number of riders with disabilities, total ridership, customer complaints, accidents, deployment costs, as well as locational aspects like the location of employment centers, schools, shopping areas, and so on. These interlacing factors make it difficult to identify optimum improvement locations without the aid of an optimization model. This dissertation proposes two integer programming models to help identify a priority list of bus stops for accessibility improvements. The first is a binary integer programming model designed to identify bus stops that need improvements to meet the minimum ADA requirements. The second involves a multi-objective nonlinear mixed integer programming model that attempts to achieve an optimal compromise among the two accessibility design standards. Geographic Information System (GIS) techniques were used extensively to both prepare the model input and examine the model output. An analytic hierarchy process (AHP) was applied to combine all of the factors affecting the benefits to patrons with disabilities. An extensive sensitivity analysis was performed to assess the reasonableness of the model outputs in response to changes in model constraints. Based on a case study using data from Broward County Transit (BCT) in Florida, the models were found to produce a list of bus stops that upon close examination were determined to be highly logical. Compared to traditional approaches using staff experience, requests from elected officials, customer complaints, etc., these optimization models offer a more objective and efficient platform on which to make bus stop improvement suggestions.

A multi-objective robust optimization model for multi-product multi-site aggregate production planning in a supply chain under uncertainty