Development of Optimization Model for Rolling Stock Utilization Planning

碩士 === 國立臺灣大學 === 土木工程學研究所 === 100 === Rolling stock is one of the most expensive assets of a railway agency or company. Therefore, efficient utilization of rolling stock is a very important objective pursued in practice. This study proposed a Rolling Stock Utilization Planning Tool to improve the e...

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Bibliographic Details
Main Authors: Kuo-Chu Liu, 劉國著
Other Authors: 賴勇成
Format: Others
Language:zh-TW
Published: 2012
Online Access:http://ndltd.ncl.edu.tw/handle/23033256402487037453
Description
Summary:碩士 === 國立臺灣大學 === 土木工程學研究所 === 100 === Rolling stock is one of the most expensive assets of a railway agency or company. Therefore, efficient utilization of rolling stock is a very important objective pursued in practice. This study proposed a Rolling Stock Utilization Planning Tool to improve the efficiency of rolling stock usage by creating a utilization schedule to cover the trips in the timetable with the consideration of practical requirements, such as inspection regulation, depot capacity, rolling stock characteristics, and most important of all, the idea of schedule circulation. Past studies usually simplified the problem by ignoring some of the important factors in practices; therefore, most of the railway agencies or companies still rely on experienced planners for this task. These practitioners can generally create an acceptable plan but there is no guarantee of the optimality. Consequently, there is a need for a planning tool which takes all important factors into account and provides optimal solutions to this problem. In order to develop such tool, this research first identified the appropriate factors by reviewing literatures and interviews with practitoners. Then the Rolling Stock Utilization Planning Model is developed to minimize the deadhead cost and inspection cost in rolling stock utilization planning cycle. This study also presents the column generation method with Gilmore-Gomory algorithm to improve the solution efficiency, especially for large-scale problem. The practical cases of Taiwan Railways Administration were used to demonstrate the validity and applicability of the proposed tool. The empirical results show that this optimization process can produce more efficient utilization plans with minimal deadhead distance and significant reduced number of inspections compared to the manual process. It’s equivalent to successfully reduce the total deadhead and inspection cost by 20%~25%. Using this decision support tool will help railways improve the efficiency of rolling stock utilization so as to provide reliable service to their customers.