OUTLINE OF A METHOD FOR ALLOCATING RAILWAY SHIFT WORKERS ACCOUNTING FOR THE DIFFICULTY OF WORK

At present, shift work is evaluated from the carriers’ perspective as employers. Therefore, the purpose of the article is to outline the characteristics of an innovative software application that would enable human resource managers to take railway workers’ satisfaction or the difficulty of a job into account when creating shift plans. This article includes an overview of the prevailing methods of handling railway shift worker scheduling and a list and description of the empirical methods for creating shifts. Next, the consideration given to the interests and preferences of employees regarding shift types is described. We then outline possible changes, especially changes utilising mathematical formulas. These patterns and considerations are verified through actual shifts and questionnaires distributed to a select group of employees. An actual shift of conductors at the Czech national carrier České dráhy is chosen for the case study. Finally, a proposal of a software system that takes employee preferences into account and permits the scheduling of blocks of free days is described. From the development point of view, the aim of this software is to achieve maximum satisfaction after subjective requirements are considered, thus ensuring, from the human resource management perspective, a higher degree of railway employees’ satisfaction, leading to better quality services and improved rail transport

A branch-and-price approach for solving the train unit scheduling problem

We propose a branch-and-price approach for solving the integer multicommodity flow model for the network-level train unit scheduling problem (TUSP). Given a train operator’s fixed timetable and a fleet of train units of different types, the TUSP aims at determining an assignment plan such that each train trip in the timetable is appropriately covered by a single or coupled train units. The TUSP is challenging due to its complex nature. Our branch-and-price approach includes a branching system with multiple branching rules for satisfying real-world requirements that are difficult to realize by linear constraints, such as unit type coupling compatibility relations and locations banned for coupling/decoupling. The approach also benefits from an adaptive node selection method, a column inheritance strategy and a feature of estimated upper bounds with node reservation functions. The branch-and-price solver designed for TUSP is capable of handling instances of up to about 500 train trips. Computational experiments were conducted based on real-world problem instances from First ScotRail. The results are satisfied by rail practitioners and are generally competitive or better than the manual ones

Modeling and Solving of Railway Optimization Problems

The main aim of this work is to provide decision makers suitable approaches for solving two crucial planning problems in the railway industry: the locomotive assignment problem and the crew scheduling problem with attendance rates. On the one hand, the focus is on practical usability and the necessary integration and consideration of real-life requirements in the planning process. On the other hand, solution approaches are to be developed, which can provide solutions of sufficiently good quality within a reasonable time by taking all these requirements into account

Evaluation of railway performance through quality of service

Railways worldwide have experienced unprecedented growth over the last decade. The infrastructure of many European railways is becoming increasingly saturated, while the operators face strong demands to increase services and carry more passengers and freight. There has been a high demand for performance improvement, to provide better service to customers. This problem is drawing increasing attention from many parties within and beyond the railway industry. In this research, the author first reviewed and analysed the existing performance measures used in railway transportation. A new generic framework for the measurement and improvement of railway network performance has been proposed, based on the concept of quality of service. The key factors affecting quality of service are identified and analysed. Secondly, the quantification of performance has been identified based on the Quality of Service framework. Multi criteria decision making has been applied to determine the weights of each Key Performance Indicator in the framework. Finally, factors within the railway system have been analysed for their impact on performance with a sensitivity analysis, to support the development of performance improvement plans. A case study has been conveyed to show the influence of the system properties on the performance measured by quality of service

Evolutionary algorithms for scheduling operations

While business process automation is proliferating through industries and processes, operations such as job and crew scheduling are still performed manually in the majority of workplaces. The linear programming techniques are not capable of automated production of a job or crew schedule within a reasonable computation time due to the massive sizes of real-life scheduling problems. For this reason, AI solutions are becoming increasingly popular, specifically Evolutionary Algorithms (EAs). However, there are three key limitations of previous studies researching application of EAs for the solution of the scheduling problems. First of all, there is no justification for the selection of a particular genetic operator and conclusion about their effectiveness. Secondly, the practical efficiency of such algorithms is unknown due to the lack of comparison with manually produced schedules. Finally, the implications of real-life implementation of the algorithm are rarely considered. This research aims at addressing all three limitations. Collaborations with DBSchenker,the rail freight carrier, and Garnett-Dickinson, the printing company,have been established. Multi-disciplinary research methods including document analysis, focus group evaluations, and interviews with managers from different levels have been carried out. A standard EA has been enhanced with developed within research intelligent operators to efficiently solve the problems. Assessment of the developed algorithm in the context of real life crew scheduling problem showed that the automated schedule outperformed the manual one by 3.7% in terms of its operating efficiency. In addition, the automatically produced schedule required less staff to complete all the jobs and might provide an additional revenue opportunity of £500 000. The research has also revealed a positive attitude expressed by the operational and IT managers towards the developed system. Investment analysis demonstrated a 41% return rate on investment in the automated scheduling system, while the strategic analysis suggests that this system can enable attainment of strategic priorities. The end users of the system, on the other hand, expressed some degree of scepticism and would prefer manual methods