Suchergebnisse

India has one of the largest rail networks in the world but has no line which can be classified as HSR allowing operational speed of 125mph. The current fastest train runs at 100 mph over a distance of only around 100 miles. However, supported by a robust political willingness, a new HSR corporation has been set up to kick-start the HSR projects from ideation to reality. Four major corridors have been identified and pre-feasibility studies have been commissioned. The first in this ambitious program is the HSR between Mumbai and Ahmedabad, two major population and commercial centers in the west of India. The success or failure of this project could show the way for future road map of HSR in India. This paper identifies and analyses the countries where HSR systems are in operation – their political, economic and social conditions relevant to HSR systems and then the features of HSR systems themselves to understand the commonalities between the nations that have opted for HSR. The objective is to identify if there is a common character or a baseline characteristic in terms of geographical, economic, political and social conditions which are essential to be a member of this exclusive club? Is there a standard financial and business model that has been adopted by these countries?Theattempt is also to compare these baseline benchmarks with those in India, to assess its strengths and weaknesses and reaffirm the chances of its success in taking up this project, one of the biggestever in its history. The results would be relevant not only for India but for all countries who aspire to be HSR countries in near future.

In any real time control system, its scheduling and control policy
should be reassessed every time the state of the system changes. In
large and complex systems, this could be a self‐defeating goal.
Implementing real time control in such systems would require an enormous
amount of computation time. Determination of discrete time interval
(simulation window length) is the main objective of this study. To
implement and demonstrate this methodology, we selected a Flexible
Manufacturing System (FMS) which approximates a dynamic job shop. The
Expert Control System (ECS) developed in this study integrated
programmes for different functions and employed multi‐pass simulation to
determine the best scheduling strategy in the system. The simulation
output is then subjected to Analysis of Variance (ANOVA) and
Newman‐Keuls′ range tests to obtain a "good" simulation
window length for different performance criteria of optimisation.