考量具有時間窗之運輸商品收益的城市物流計畫方法;A planning method of city logistics considers the benefits of shipping commodities with time windows

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Title:	考量具有時間窗之運輸商品收益的城市物流計畫方法;A planning method of city logistics considers the benefits of shipping commodities with time windows
Authors:	陳品蓉;Chen, Pin-Rong
Contributors:	企業管理學系
Keywords:	城市物流;電動車;顧客滿意度;深度優先搜索;遞迴;貪婪策略;City logistics;Electric Vehicles;Depth-first search;Recursive;Greedy strategy
Date:	2022-06-28
Issue Date:	2022-07-13 18:41:56 (UTC+8)
Publisher:	國立中央大學
Abstract:	因應電商營業模式的快速興起，快速膨脹的需求量間接影響物流的配送，物流運輸最主要的服務內容是商品的運輸，且服務性質不像以往沒有時間上的限制。因此本研究以城市物流配送下產生的顧客滿意度為主軸，提出具有軟時間窗約束的車輛途程問題，並將每個顧客的時間窗約束視為一個懲罰函數，當物流配送不滿足顧客指定時間窗時，商品價值收益則給予打折回饋，作為補償顧客滿意增加顧客忠誠度。在此條件下，物流業者該如何追求商品價值收益最大化之物流配送路徑，本研究方法演算過程中使用深度優先搜尋法 (Depth-first Search) 計算路徑運送節點以及遞迴 (Recursive) 列舉所有可能路徑集合，將形成初始解之集合執行貪婪策略，並捨棄不滿足限制式條件之路徑，最終結果為最佳配送路徑。本研究最後，利用美國量販店 Target實際案例展示演算法規劃成果。;In response to the rapid growth of the e-commerce business model, the expanding demand indirectly affects the logistics distribution. The purpose of the study was to discuss the value of goods generated under the city logistics distribution for the vehicle routing problem with soft time window constraints. The time window constraint for each customer is treated as a penalty function, which is very general in the sense that it can be non-convex and discontinuous as long as it is piecewise linear. In this algorithm, the depth-first search method is used in the calculation process in order to calculate the route transport nodes. Then use the recursive to enumerate all possible route as the initial solution sets. After that, we must determine the delivering times of processing at customers so that the total penalty is minimized. By using the greedy strategy discard the routes that do not satisfy the restriction. At the end of this study, the actual case of a retailer named Target in the United States is used to demonstrate the algorithm and report computational results.
Appears in Collections:	[Graduate Institute of Business Administration] Electronic Thesis & Dissertation

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