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  • 學位論文

臺鐵車輛調配規劃決策支援模式之研發

Development of the Decision-Support Model for Rolling Stock Assignment in Taiwan Railways Administration

指導教授 : 賴勇成

摘要


軌道車輛為鐵路營運中最昂貴的設備之一,因此如何有效運用此項資產,以達成高效率之「車輛資源運用規劃」,將對整體系統營運產生重要之影響。本研究旨在分析車輛資源運用規劃中之「調配規劃」,以一機務段為單位,根據運用表與段檢修容量與人力、配屬車型車數等資訊、以及相關對應之檢修規章,進行段內車輛調配作業,除需滿足每日運用路徑營運旅次需求外,同時還要滿足各型車輛各級檢修規定。實務作業中,調配作業人員多透過以往工作經驗手動進行規劃,然其結果僅能歸為一可行解,難保障為最有效率之車輛運用計畫。綜觀過去文獻,相關探討為數不多,且由於世界各國現行鐵路營運制度上之差異,所面對的問題層面本質上並不相同,故難以從中歸納出得實際運用並輔助在實務作業上之決策支援模式。 本研究首先透過文獻回顧分析與專家實務訪談,彙整了車輛調配規劃在整體車輛資源運用規劃所扮演之角色與重要性,並依據實務概念建立人工調配模式,透過電腦自動化輔助現行臺鐵人工作業流程,其後深究其問題之核心本質並另建立完整之最佳化調配模式,然由於該模式求解時間不符實務應用所需,本研究於是結合實務與最佳化概念,提出簡化最佳化模式與啟發式模式,並經由臺鐵新竹機務段之實務案例進行模式之分析與驗證。由案例分析結果得知,簡化最佳化模式與啟發模式可大幅增進求解效率,且產出與完整模式相當品質之規劃;而與人工調配模式比較之結果,簡化模式與啟發式模式在檢修次數上均減少5.41%,使用率分別有4.87%與4.98%之提升;若加入車輛之事故率之隨機情況考量探討,啟發式模式之檢修次數較人工求解減少20%,而使用率仍維持有4.78%之改善。研究成果貼近實務並有顯著改善,將可支援實務作業人員車輛配規劃決策之用。

並列摘要


The railway rolling stock is one of the expensive assets of all railway companies around the world. The proper arrangement of operation and inspection is therefore the key to determine the life of the rolling stock. This arrangement is commonly known as the rolling stock assignment (RSA) planning, which aims to assign appropriate rolling stock to cover a given set of table of utilization path, while taking maintenance (or inspection), depot capacity, and other relevant rules for circulation into consideration. This research first develops an automation model to automate the RSA process according to the concept of manual process implemented in Taiwan Railways Administration. An exact optimization model is then developed by minimizing cost associated with the assignment process by considering all regulations and practical constraints. To improve the solution efficiency, the simplified and heuristics model are further developed to accelerate the planning process while maintaining the solution quality. The results from the real case of Hsinchu Depot indicate that the number of inspections decreases by 5.41% in both simplified and heuristics model comparing with automation model, and average usage rate improves by 4.87% and 4.98%, respectively. The manual and heuristics model are further compared by a case with unexpected rolling stock failure during the planning horizon. The results show that the number of inspections can be reduced by 20% in the heuristics model, and average usage rate can still be improved by 4.78%. Both simplified and heuristics models have proven that they can not only to generate more effective plans than manual process, but also reduce solution time and human resources.

參考文獻


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