An eigenmodel for iterative line planning, timetabling and vehicle scheduling in public transportation

Prelims

In the planning process of railway companies, we propose to integrate important decisions of network planning, line planning, and vehicle scheduling into the task of periodic timetabling. From such an integration, we expect to achieve an additional potential for optimization.Models for periodic timetabling are commonly based on the Periodic Event Scheduling Problem (PESP). We show that, for our purpose of this integration, the PESP has to be extended by only two features, namely a linear objective function and a symmetry requirement. These extensions of the PESP do not really impose new types of constraints. Indeed, practitioners have already required them even when only planning timetables autonomously without interaction with other planning steps. Even more important, we only suggest extensions that can be formulated by mixed integer linear programs.Moreover, in a self-contained presentation we summarize the traditional PESP modeling capabilities for railway timetabling. For the first time, also special practical requirements are considered that we prove not being expressible in terms of the PESP.KeywordsCrew ScheduleConstraint GraphSingle TrackLinear Objective FunctionLine PlanningThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

In this chapter, we integrate line planning, timetabling, passenger routing, and vehicle scheduling, using the results of Chapters 2, 3, and 4. We present an optimization model as well as some computational results and analyze its structure in regard to computational performance.

The need to ensure adequate numbers of motivated health professionals is at the forefront of the modernisation of the UK NHS. The aim of this paper is to assess current understanding of the labour supply behaviour of nurses, and to propose an agenda for further research. In particular, the paper reviews American and British economics literature that focuses on empirical econometric studies based on the classical static labour supply model. American research could be classified into first generation, second generation and recent empirical evidence. Advances in methods mirror those in the general labour economics literature, and include the use of limited dependent variable models and the treatment of sample selection issues. However, there is considerable variation in results, which depends on the methods used, particularly on the effect of wages. Only one study was found that used UK data, although other studies examined the determinants of turnover, quit rates and job satisfaction. The agenda for further empirical research includes the analysis of discontinuities in the labour supply function, the relative importance of pecuniary and non-pecuniary job characteristics, and the application of dynamic and family labour supply models to nursing research. Such research is crucial to the development of evidence-based policies.

Providing attractive and efficient public transport services is of crucial importance due to higher demands for mobility and the need to reduce air pollution and to save energy. The classical planning process in public transport tries to achieve a reasonable compromise between service quality for passengers and operating costs. Service quality mostly considers quantities like average travel time and number of transfers. Since daily public transport inevitably suffers from delays caused by random disturbances and disruptions, robustness also plays a crucial role. While there are recent attempts to achieve delay-resistant timetables, comparably little work has been done to systematically assess and to compare the robustness of transport plans from a passenger point of view. We here provide a general and flexible framework for evaluating public transport plans (lines, timetables, and vehicle schedules) in various ways. It enables planners to explore several trade-offs between operating costs, service quality (average perceived travel time of passengers), and robustness against delays. For such an assessment we develop several passenger-oriented robustness tests which can be instantiated with parameterized delay scenarios. Important features of our framework include detailed passenger flow models, delay propagation schemes and disposition strategies, rerouting strategies as well as vehicle capacities. To demonstrate possible use cases, our framework has been applied to a variety of public transport plans which have been created for the same given demand for an artificial urban grid network and to instances for long-distance train networks. As one application we study the impact of different strategies to improve the robustness of timetables by insertion of supplement times. We also show that the framework can be used to optimize waiting strategies in delay management.

We are more and more close to the time when a higher number of autonomous vehicles are appearing in road traffic. The number of unanswered questions does not diminish but grow. One such issue is the role of autonomous vehicles in public transport. When talking about autonomous vehicles we often think of only cars and we think less about self-driving buses. But the economic potential inherent in autonomous buses is huge. In the Hungarian vehicle and crew scheduling practice (and also in other countries) the one driver-one vehicle control is typical. This method closely links the vehicles and the drivers. Vehicles should therefore adapt to the rest time of the crew and the employment rules. Unused reserves are generated in the system. Autonomous vehicles can release this overcapacity. Thanks to that, fewer vehicles can carry out public transport tasks and we can save extra rides. It also provides a solution to the lack of drivers, which is a basic problem in many countries. In our study we show the reserves that can be recovered from the system in the case of three Hungarian cities (Eger, Dunaujvaros, Győr). We show how much savings can be achieved by running autonomous buses in European cities with a population of 45 000, 54 000 and 130 000 inhabitants. The results are promising. In smaller cities we could achieve about 20% of economical savings but in bigger cities 40% is also realistic. Our statements are based on only rough calculations and they try to help in preparation for the future.

The scope of this volume centers on advancements in the state of art and the state of the practice in computer-aided systems in public transport. Yet, this volume illustrates a greater breadth of subjects in this area. The common theme remains the use of computer-aided methods and operations research techniques to improve: (1) information management; (2) network and route planning; (3) vehicle and crew scheduling and rostering; (4) vehicle monitoring and management; and, (5) practical experience with scheduling and public transport planning methods. This volume consists of selected papers presented at the Ninth International Conference on Computer-Aided Scheduling of Public Transport.

This paper examines time windows for scheduled trips in multiple depot vehicle and crew scheduling problems that arise in public bus transportation. In practice, the two planning tasks vehicle scheduling and crew scheduling are traditionally solved sequentially with the implicit understanding that the scheduled time for timetabled trips remains fixed. In order to improve cost efficiency two concepts have been developed over the last years: In order to obtain better flexibility when scheduling crews, vehicle and crew scheduling problems are tackled simultaneously. In order to extend flexibility while scheduling vehicles, variable trip departure and arrival times are considered. Obviously the combination of both concepts promises the largest savings, but probably leads to bursting computational times due to growing problem complexity. In this paper we combine both concepts by extending the integrated vehicle and crew scheduling problem with the possibility to shift scheduled trips within defined time windows. We examine the tradeoffs between solution quality and computational time for different solution approaches.

Chapter 5 - Planning and Tender Schedule Stages

The urban transport planning process has four main activities: Network design, Timetable construction, Vehicle scheduling and Crew scheduling; each activity has subactivities. In this paper the authors work with the subactivities of timetable construction: minimal frequency calculation and departure time scheduling. The authors propose to solve both subactivities in an integrated way. The developed mathematical model allows multi-period planning and it can also be used for multimodal urban transportation systems. The authors consider demand uncertainty and the authors employ fuzzy programming to solve the problem. The authors formulate the urban transportation timetabling construction problem as a bi-objective problem: to minimize the total operational cost and to maximize the number of multi-period synchronizations. Finally, the authors implemented the SAUGMECON method to solve the problem.

Line planning is an important part of service management of Railway. Using the minimum operating cost as objective function, an integer linear programming model for line planning problem of intercity railway is established in this paper. Different alternative line set are constructed according to different train stopping patterns of intercity railways to investigate the impact of different train stopping strategies on rail line capacity utilization and passenger service level. A case study is carried out with Guangzhou-Zhuhai intercity railway as a background. The results show, train stopping pattern plays an important role at the stage of line planning and it will affect a train line plan from interval, equilibrium and other aspects of service quality.

E-commerce has become the mainstream consumption mode for people, and with the continuous increase of online shopping business volume, controlling logistics costs has become an urgent problem to be solved. In order to solve the challenges in vehicle scheduling and achieve a scientific and reasonable vehicle scheduling scheme, this research is based on Hadoop Big data platform, introduces the concept of time axis, and builds a vehicle scheduling model based on Hadoop intelligent platform. Based on quantum genetic algorithm and combined with MapReduce model, a quantum improved genetic algorithm is constructed to solve vehicle scheduling optimization problems. The results show that the traditional quantum genetic algorithm converges after 20 iterations, achieving an optimal value of 575 and taking 360 seconds. The improved quantum genetic algorithm converged after 10 iterations and achieved an optimal value of 675, taking 200 seconds. Compared with quantum genetic algorithm, the improved quantum genetic algorithm reduces the time spent by 44.4%. Selecting customer data from a certain logistics company for testing, the improved algorithm shortens the delivery time and achieves the design of the optimal path scheduling plan. This study optimized transportation routes and resource scheduling, reduced transportation costs, and played an important role in optimizing vehicle scheduling in the logistics industry.

The literature on how network-based incubation influences the performance of technology-based start-ups has recently grown considerably and provided valuable insights. However, at the same time this literature has become quite fragmented, inconsistently conceptualised, and theoretically underdeveloped. Therefore, this article uses three management theories to structure the literature, improve the theoretical underpinning and develop an agenda for further research. The management theories are the resource-based view, knowledge-based view, organisational learning, and social capital theory. We find that the network-based incubation literature has convincingly shown that network-based incubation provides start-ups with resources, capabilities, knowledge, learning and social capital. However, the influence of these intermediary benefits on start-up performance is ambiguous. There is a considerable opportunity to advance the network-based incubation literature with contemporary insights from management theories. We propose an agenda for further research on network-based incubation that leads to a fine-grained model of the mechanisms and impact of network-based incubation that goes beyond taken for granted assumptions about the positive impact of network-based incubation.

Background Given the recognised relationship between poverty, welfare provision and health, welfare rights advice has emerged as a potentially key intervention in improving health and reducing inequalities. The generation of evidence in this area has proven difficult however, creating a need to take stock of existing research and develop an agenda for future work. Methods A series of four workshops was convened involving researchers from four UK universities who had previously undertaken work examining the relationship between welfare advice and health, from a range of methodological perspectives. Run concurrently to a scoping of the literature, these workshops aimed to synthesise lessons from prior research; formulate outstanding research questions; and outline potential methodological approaches for addressing these. A survey was undertaken with professionals (from welfare or legal advice sectors, the health sector, commissioning, local government, and housing services, n = 50) to test out, refine and add to these research questions. Results Key research questions developed from these workshops were: Are there inequalities in the impact and reach of advice services across social groups? How/ does advice delivery mode matter?What are the individual and system level impacts of the de-implementation of advice services?What are the impacts of changes to welfare provision on children, inter-generationally and throughout the life course?How do experiences of social welfare vary by social group, geographically and across generations? How do different identities combine to influence how social welfare is understood? Conclusions While the collaborative process brought challenges in balancing research and practitioner expertise, this model of working has been successful in setting an agenda for further research with maximum utility to practice. Direct outputs from the projects have been the collaborative submission of a journal article and a research bid. Key messages The collaboration, which was supported by the NIHR School of Public Health Research, led to the establishment of a concise research agenda. Through extensive stakeholder consultation, this will have maximal utility for practice.

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