現今，提供隔日送達服務的物流業者 (overnight carriers) 必須尋求穩定的訂單來維持他們的競爭優勢。另一方面，物流業者也持續專注在培養處理即時性 (real-time) 需求的能力。盡可能滿足客戶的需求同時維持具競爭力的營運成本，是這類業者的共同目標。
本篇論文的目的在建立一個包含時間窗限制的機率性旅行推銷員問題(Probabilistic Traveling Salesman Problem with Time Window Constraints, PTSPTW) 模式來處理機率性的需求。同時為了維持先驗 (a priori) 途程的彈性以應付未來可能發生的立即需求，模式中也導入了雙重時區 (Double Horizon) 的概念。我們提出了一個兩階段的啟發式演算法來處理這樣的問題。在此研究中發現，面對包含即時性需求的具時間窗限制之機率性旅行推銷員問題，尤其是即時性需求所佔比重較高的案例，維持先驗途程的彈性不但能夠滿足更多客戶的需求，更有助於降低車輛在途程中的總旅行時間。此外，在時間窗較狹窄與客戶需求機率較高的問題之中，具有較大彈性的先驗途程相對上也具有較大的優勢。

Nowadays, in order to keeping competitive advantages, overnight carriers are searching for more stable orders. On the other hand, carriers also concentrate on developing abilities to deal with real-time demands continuously. The common goal of overnight carriers is satisfying needs of customers as possible while keeping operating costs competitive.
The purpose of this thesis is to construct a Probabilistic Traveling Salesman Problem model with Time Window constraints (PTSPTW) to cope with probabilistic demands. Meanwhile, the idea of Double Horizon is incorporated into the model to maintain the flexibility of the a priori route for future possible immediate requests. A two stage heuristic algorithm is proposed to solve the PTSPTW. The conclusion is that the flexibility of the a priori route is helpful not only to satisfy more demands but also to reduce total traveling time of the vehicle in the problem with real-time demands, especially the cases which the weight of real-time demands is high. Besides, in the problems with narrow time window or high request probabilities, the a priori route with more flexibility has more advantages.

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