複合式運輸在國際運輸上為一主要之運輸方式，其結合了兩種以上的載具，使得運輸可以在有效的在時間內完成，而物流業者所提供的貨櫃基於可能配給其他客戶使用，使得每個客戶能使用的貨櫃數量為隨機的，故客戶能使用的貨櫃數量為多階狀態且對應一機率分配。本研究建構了多階狀態之複合式運輸網路 (multistate intermodal logistics network, MILN)模型，此網路包含了節點 (node) 與傳輸邊 (route)，其中節點代表集貨站(cargo terminal)或轉運站 (transit station)，而傳輸邊則為連接節點的路線。傳輸邊上的配送時間包含了服務時間、旅行時間以及等候時間，因載具的不同以及所裝載貨櫃的多寡所影響，而載具到達轉運站的時間必須在時窗(time windows)之內，也就是在最早允許收貨之時間到最晚允許收貨之時間內到達。此外，在商品配送的過程中，可能因商品本身保存、搬運造成的碰撞或交通事故等因素，造成客戶需求數量無法滿足，故除配送時間因素外，將商品配送損壞 (delivery spoilage)也為評估運輸的重要考量，因此本研究提出一網路可靠度 (network reliability)做為運輸性能指標用以評估時窗、配送損壞條件下之多階狀態之複合式運輸網路，其中網路可靠度之定義為在時窗條件下成功運輸市場需求量之機率。本研究首先於第三章提出一演算法求得滿足市場需求及時間限制之網路可靠度，透過一實際案例探討機車零件運輸演示所提出之演算法。接著，為了更貼近真實的物流狀況，本論文進一步將商品配送損壞 (delivery spoilage)納入考量，並於第四章發展一考量配送損壞之演算法，並且在前章所提實務案例中，納入損壞率之考量。於決策觀點，管理決策者可運用所提出兩演算法求算網路可靠度，此績效指標有助於瞭解多階狀態複合式運輸網路之整體運輸性能並可提供業者作為運輸的決策與分析。

Network structures have been diffusely adopted in logistics systems where the delivery to be completed within the promised time frame is specifically the most critical target. This paper focuses on a multistate intermodal logistics network (MILN) with transit stations, cargo terminals and routes. Along each route, there is a carrier whose available containers is multistate because the containers could be occupied by other customers. Besides, the delivery time consisting of service time, travel time, and waiting time varies with the number of containers and the type of vehicle. The arrival time at cargo terminal should be within the time window which is the interval between the earliest and latest acceptable arrival time. This paper is mainly to evaluate network reliability. Such network reliability can be treated as a delivery performance index. An algorithm is then proposed in chapter 3 to calculate network reliability and a practical case of starting motor distribution between Taiwan and China is presented to emphasize the managerial implication of network reliability. Moreover, commodities may be spoilt during delivery due to traffic accidents, collisions, natural disasters, weather, etc., and thus the intact commodities may not satisfy the market demand. An algorithm is further developed in chapter 4 to find the network reliability, the probability that the MILN can successfully deliver sufficient commodities to meet market demand under the time windows and delivery spoilage. Same case is utilized to illustrate the proposed algorithm. From the decision-making viewpoint, supervisors can evaluate network reliability by proposed algorithms and presented to emphasize the management implication.

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