Computer Based Train Schedule Optimize for Addis Ababa LRT System
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Date
2015-04
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Addis Ababa University
Abstract
This research paper work focuses on passenger train schedule modeling; scheduling algorithm which is used to solve the modeled problem and on the deployment of computer Based Train Schedule Optimizer (CBTSO) for Addis Ababa Light Rail Transit (LRT) system.
In railway system the guided movement of trains with highly sensitive safety issues together with the expensive nature of trains, railway infrastructures and train crews make the requirement of train and crew schedules inevitable. Schedules are the way to efficiently utilize the available railway resources and meet different constraints like traffic and operator’s requirement constraints. There are two methods of scheduling namely manual scheduling (the traditional method) and computer based scheduling.
For more than 150 years, traditional scheduling was the typical scheduling method used in almost all railways found in the world. Only the occurrence of high performance computers in the 1990s and the advancements in the operation research methods and artificial intelligence methods offered the opportunity to introduce computer based scheduling methods.
Manual based train schedule requires skilled and experienced rail network planners. Further it requires a massive mental effort and takes long time to solve the problem. Further there is a rare chance to find such human powers in a newly starting railway companies like Ethiopian Railway Corporation (ERC). Considering these into account this research work concentrates to develop a Computer Based Train Schedule Optimizer (CBTSO) for Addis Ababa LRT which is currently in its final project stage.
In this paper a mathematical model used to formulate train schedule problem and the corresponding algorithm suitable to solve the schedule problem for Addis Ababa LRT system are presented. Eventually, a computer program that is planned to implement the algorithm will be discussed.
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Keywords
CBTSO, LRT, modeling, algorithm, Schedule, Optimization