考量具有時間窗之運輸商品收益的城市物流計畫方法

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姓名

陳品蓉(Pin-Rong Chen) 查詢紙本館藏

畢業系所

企業管理學系

論文名稱

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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至系統瀏覽論文 (2027-7-1以後開放)

摘要(中)

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。

摘要(英)

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.

關鍵字(中)

★ 城市物流
★ 電動車
★ 顧客滿意度
★ 深度優先搜索
★ 遞迴
★ 貪婪策略

關鍵字(英)

★ City logistics
★ Electric Vehicles
★ Depth-first search
★ Recursive
★ Greedy strategy

論文目次

摘要
ABSTRACT
目錄
圖目錄
表目錄
第 1 章、緒論.......................... 1
1.1 研究背景與動機.......................... 1
1.2 研究目的.......................... 1
1.3 研究範圍.......................... 2
1.4 研究方法與步驟.......................... 2
第 2 章、相關研究探討.......................... 3
2.1 城市物流.......................... 3
2.2 顧客滿意度.......................... 6
2.3 電動車輛.......................... 8
第 3 章、模型發展.......................... 13
3.1 問題情境說明.......................... 13
3.2 數學規劃模型.......................... 16
3.3 演算概念與其運用原理.......................... 19
3.4 求解流程圖.......................... 26
3.5 求解演算法.......................... 29
第 4 章、應用實例.......................... 36
4.1 實際操作.......................... 36
4.2 實務應用.......................... 48
第 5 章、結論與後續研究議題.......................... 54
5.1 結論.......................... 54
5.2 後續研究議題.......................... 55
參考文獻.......................... 56
附錄 (一).......................... 60
附錄 (二).......................... 63

參考文獻

Anderson, E.W., Fornell, C., & Rust, R. (1997). Customer satisfaction, productivity, and profitability: differences between goods and services. Marketing Science, 16(2), 129–145.

Barkaoui, M., Berger, J., & Boukhtouta, A. (2015). Customer satisfaction in dynamic vehicle routing problem with time windows. Applied Soft Computing, 35, 423-432.

Brandstatter, G., Leitner, M., & Ljubic, I. (2020). Location of Charging Stations in Electric Car Sharing Systems. Transportation Science, 54(5), 1408–1438.

Chan, C. (2007). The state of the art of electric, hybrid, and fuel cell vehicles. Proceedings of the IEEE, 95(4), 704–718.

Crainic, T.G., Perboli, G., Mancini, S., & Tadei, R. (2010). Two-Echelon Vehicle Routing Problem: A satellite location analysis. Procedia - Social and Behavioral Sciences, 2(3), 5944-5955.

Crainic, T.G. (2014). City Logistics. INFORMS Tutorials in Operations Research, 181-212.

Dantzig, GB., & Ramser, JH. (1959). The truck dispatching problem. Management Science, 6(1), 80–91.

Desrochers, M., & Laporte, G. (1991). Improvements and extensions to the Miller-Tucker-Zemlin subtour elimination constraints. Operations Research Letters, 10(1), 27-36.

Den Boer, E., Aarnink, S., Kleiner, F., & Pagenkopf, J. (2013). Zero emission trucks: An overview of state-of-the-art technologies and their potential. CE Delft, Delft, Netherlands.

Doucette, R.T., & McCulloch, M.D. (2011). Modeling the prospects of plug-in hybrid electric vehicles to reduce CO2 emissions. Applied Energy, 88(7), 2315–2323.

Erdogan, S., & Miller-Hooks, E. (2012). A Green Vehicle Routing Problem. Transportation Research:Part E, 48(1), 100–114.

Fiori, C., Ahn, K., & Rakha, H. (2016). Power-based electric vehicle energy consumption model: Model development and validation. Applied Energy, 168, 257–268.

Gargari, E.A., & Lucas, C. (2007). Imperialist Competitive Algorithm: An Algorithm for Optimization Inspired by Imperialistic Competition. IEEE Congress on Evolutionary Computation(CEC), 4661-4667.

Groër, C., Golden, B., & Wasil, E. (2009). The Consistent Vehicle Routing Problem. Manufacturing and service operations management, 11(4), 630–643.

Holland, J.H. (1975). Adaptation in Natural and Artificial Systems: an introductory analysis with applications to biology, control, and artificial intelligence. University of Michigan Press.

Hu, H., Li, X., Zhang, Y., Shang, C., & Zhang, S. (2019). Multi-objective location-routing model for hazardous material logistics with traffic restriction constraint in inter-city roads. Computers & Industrial Engineering, 128, 861-876.

Ibaraki, T., Imahori, S., Kubo, M., Masuda, T., Uno, T., & Yagiura, M. (2005). Effective Local Search Algorithms for Routing and Scheduling Problems with General Time-Window Constraints. Transportation Science, 39(2), 206-232.

Knowles, M., Scott, H., & Baglee, D. (2012). The effect of driving style on electric vehicle performance, economy and perception. Int. J. Electric and Hybrid Vehicles, 4(3), 228–247.

Kobayashi, Y., Kiyama, N., Aoshima, H., & Kashiyama, M. (2011). A route search method for electric vehicles in consideration of range and locations of charging stations. IEEE Intelligent Vehicles Symposium.(IV), 920–925.

Larminie, J., & Lowry, J. (2003). Electric Vehicle Technology Explained, UK, Wiley, Chichester.

Lee, Y.K., Lee, C.K., Lee, S.K., & Babin, B.J. (2008). Festivalscapes and patrons’ emotions, satisfaction, and loyalty. Journal of Business Research, 61(1), 56-64.

MacLean, H.L., & Lave, L.B. (2003). Evaluating automobile fuel/propulsion system technologies. Progress in Energy and Combustion Science, 29(1), 1–69.

Muratori, M., Moran, M.J., Serra, E., & Rizzoni, G. (2013). Highly-resolved modeling of personal transportation energy consumption in the United States. Energy, 58, 168–177.

Nagata, Y., Braysy, O., & Dullaert, W. (2010). A penalty-based edge assembly memetic algorithm for the vehicle routing problem with time windows. Computers & Operations Research, 37(4), 724-737.

Nagy, G., Wassan, N., Speranza, G., & Archetti ,C. (2015). The Vehicle Routing Problem with Divisible Deliveries and Pickups. Transportation Science, 49(2), 271-294.

Nesterova, N., Quak, H., Balm, S., Roche-Cerasi, I., & Tretvik, T. (2013). FREVUE D1.3 State of the art city logistics and EV: State of the art of the electric freight vehicles implementation in city logistics. European Commission Seventh framework programme.

Oliver, R.L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17, 460-469.

Pollet, B.G., Staffell, I., & Shang, J.L. (2012). Current status of hybrid, battery and fuel cell electric vehicles: From electrochemistry to market prospects. Electrochimica Acta, 84, 235–249.

Poole, D., & Mackworth, A. (2017). Artificial Intelligence: foundations of computational agents. pp. 90-120, USA, Cambridge University Press.

Qian, J., & Eglese, R. (2015). Fuel emissions optimization in vehicle routing problems with time-varying speeds. European Journal of Operational Research, 248(3), 840–848.

Solomon, M.M. (1987). Algorithms for the vehicle routing and scheduling problems with time window constraints. Operational Research, 35(2), 254-265.

Sweda, T.M., Dolinskaya, I.S., & Klabjan, D. (2016). Optimal recharging policies for electric vehicles. Transportation Science. 51(2), 1-23.

Tie, S.F., & Tan, C.W. (2013). A review of energy sources and energy management system in electric vehicles. Renewable and Sustainable Energy Reviews, 20, 82–102.

U.S. Department of Energy. (2012). Plug-in electric vehicle handbook for fleet managers. Office of Energy Efficiency and Renewable Energy, National Renewable Energy Laboratory(NREL).

U.S. Department of Energy. (2013). Clean cities guide to alternative fuel and advanced medium- and heavy-duty vehicles. Office of Energy Efficiency and Renewable Energy, National Renewable Energy Laboratory (NREL).

Winkelhake, U. (2018). The Digital Transformation of the Automotive Industry. Switzerland, Springer International Publishing AG. pp.96-98.

Woodruff, R.B., Cadotte, E.R., & Jenkins, R.L. (1983). Modeling consumer satisfaction processes using experience-based norms. Journal of Marketing Research, 20, 296-304.

Xu, X., Hao, J., & Zheng, Y. (2020). Multi-objective artificial bee colony algorithm for multi-stage resource leveling problem in sharing logistics network. Computers and Industrial Engineering, 142, 106338.

Xu, X., Wang, C., & Zhou, P. (2021). GVRP considered oil-gas recovery in refined oil distribution: From an environmental perspective. International Journal of Production Economics, 235, 108078.

Yilmaz, M., & Krein, P.T. (2013). Review of battery charger topologies, charging power levels, and infrastructure for plug-in electric and hybrid vehicles. IEEE Transactions on Power Electronics, 28(5), 2151–2169.

指導教授

呂俊德

審核日期

2022-6-28

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