隨機需求下軌道基礎設施投資選擇模組之研發與應用

A Multi-period Investment Selection Model For Strategic Railway Capacity Planning Under Stochastic Demand

施美成(Mei-Cheng Shih)

指導教授 ： 賴勇成

國立臺灣大學/工學院/土木工程學研究所/碩士(2010年)

https://doi.org/10.6342/NTU.2010.00904

摘要

近年來世界各國軌道系統的使用量大幅成長，同時對容量的需求也大幅提升，又由於未來的需求量十分龐大，因此軌道營運業者必須考慮升級軌道硬體設施以增加系統容量。本研究根據數學規劃方法和穩健性最佳化技巧，研發一軌道系統多期投資選擇模組，並利用班式分解法有效率的求解這個問題。根據未來預估的不確定性需求，可用資金和可使用硬體擴充方案，多期投資選擇模組可以決定一個最佳的多期投資計畫。此投資計畫可協助規劃人員決定路網容量升級的地點、時間與方法。這個決策支援工具可協助軌道營運單位提升容量升級的效益與提供顧客更穩定與優良的運輸服務。

關鍵字

鐵路運輸 ； 容量規劃 ； 決策支援 ； 班式分解法 ； 整數規劃

並列摘要

The potential growth of the railway traffic is expected to be substantial worldwide; hence railway companies and agencies are looking for better tools to allocate their capital investments on capacity planning in the best possible way. In this research I develop a Multi-period Investment Selection Model (MISM) by using robust optimization and multi-commodity flow techniques. The MISM is then decomposed by using Bender’s decomposition to efficiently obtain the optimal solution. Based on the estimated future demand, available budget and expansion options, MISM can determine the multi-period optimal investment plan regarding which portions of the network need to be upgraded with what kind of capacity improvements at each defined period in the decision horizon. Using this decision support tool will help railway companies or agencies maximize their return from capacity expansion projects and thus be better able to provide reliable service to their customers, and return on shareholders’ investment.

並列關鍵字

Railway Transportation ； Capacity Planning ； Decision Support ； Bender’s Decomposition ； Integer Programming

參考文獻

Benders, J. F. (1962). Partitioning procedures for solving mixed-variables programming problems, Numerische Mathematik, Vol. 4.

Birge, R. J. (1995). Current Trends in Stochastic Programming Computation and Applications, Department of Industrial and Operation Engineering, University of Michigan Ann Arbor, Michigan 48109-2117.

Birge, J. R. and F. Louveaux (1997). Introduction to Stochastic Programming, Springer Verlag.

Dantzig, G. B. 1955. Linear programming under uncertainty. Mgmt. Sci, 1, 197-206.

Delorme, X., J. Rodriguez, and X. Gandibleux (2001). Heuristics for railway infrastructure saturation, Theoretical Computer Science, Vol 50(1), 39-53.