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

Multi-criteria decision making for group decision support system

Group Decision Support System (GDSS) is suitable if used in decision-related meeting as a medium for them to share ideas, extract and analyze the information, and making decision. However, making decision is more complex where multiple criteria, conflict, and judgment need to be considered, which referred to as Multi-Criteria Decision Making (MCDM). Therefore, a suitable technique is preferred to solve the multi-criteria problem in GDSS. Many authors have developed fuzzy AHP method in order to solve MCDM problem because of its ability to extend the strength of Analytical Hierarchy Process (AHP) with fuzzy set theory which able to consider vagueness and both quality and quantity factors. In spite of its strength and ability to solve MCDM problem, fuzzy AHP still contains mathematical calculations which is considered quite complicated for some people, and lack of voting opportunity for the decision makers. Thus, another method in MCDM is introduced here, which is the Social Choice (SC) method along with its ability to give opportunity of voting for the decision makers. In this study, the author will append the SC method in the last steps of fuzzy AHP decision making process in order to let the decision makers to directly involve in the most important part of decision making