GIS를 이용한 최적 도심 유통 네트워크 설계 : 몽골 울란바타르 내 우유 산업 사례 Designing the Optimal Urban Distribution Network using GIS : Case of Milk Industry in Ulaanbaatar Mongolia원문보기
말단배송최적화는 도심내 공급사슬의 운영의 핵심적인 역할을 수행하고 있으며, 전체 배송 프로세스에서 가장 복잡하고 많은 비용을 지불해야만 한다. 도심복합물류센터 (Urban Consolidation Center: UCC)는 최근 말단배송 서비스를 운영하고 고객의 수요를 만족시키기 위한 핵심적인 자산으로 인식되고 있다. UCC를 활용할 경우 도심 내 다양한 요인을 고려하여 최적의 배송 과정을 설계함으로써 배송에 소요되는 시간과 이동거리를 최소화할 수 있다는 장점이 존재한다. 본 연구에서는 지리정보시스템 (GIS)를 활용하여 다양한 수리모형이 통합된 시나리오 분석을 활용하기 위한 기법을 제안한다. 특히, 본 연구는 몽골의 수도 울란바타르를 사례로 실제 도심 내 최적 배송네트워크를 설계하는 것을 목표로하고 있다. 이를 위해 위치배분문제와 차량경로문제를 결합하는 기법을 제안하였다. UCC의 위치와 개수를 기반으로 다양한 시나리오를 설계하였으며, 기본적인 총배송거리, 배송시간, UCC의 수 및 필요 차량의 수를 기준으로 시나리오를 평가하였다. 또한, UCC의 건설과 운영에 필요한 전체 비용 관점에서 최적의 시나리오를 비교 선정하였다. 본 연구의 결과는 도심 내 말단 배송을 위한 유통 네트워크를 설계해야 하는 관리자 혹은 정부 기관의 담당자들이 합리적인 의사결정을 내리기 위한 객관적인 근거 자료로 활용될 수 있을 것이다.
말단배송최적화는 도심내 공급사슬의 운영의 핵심적인 역할을 수행하고 있으며, 전체 배송 프로세스에서 가장 복잡하고 많은 비용을 지불해야만 한다. 도심복합물류센터 (Urban Consolidation Center: UCC)는 최근 말단배송 서비스를 운영하고 고객의 수요를 만족시키기 위한 핵심적인 자산으로 인식되고 있다. UCC를 활용할 경우 도심 내 다양한 요인을 고려하여 최적의 배송 과정을 설계함으로써 배송에 소요되는 시간과 이동거리를 최소화할 수 있다는 장점이 존재한다. 본 연구에서는 지리정보시스템 (GIS)를 활용하여 다양한 수리모형이 통합된 시나리오 분석을 활용하기 위한 기법을 제안한다. 특히, 본 연구는 몽골의 수도 울란바타르를 사례로 실제 도심 내 최적 배송네트워크를 설계하는 것을 목표로하고 있다. 이를 위해 위치배분문제와 차량경로문제를 결합하는 기법을 제안하였다. UCC의 위치와 개수를 기반으로 다양한 시나리오를 설계하였으며, 기본적인 총배송거리, 배송시간, UCC의 수 및 필요 차량의 수를 기준으로 시나리오를 평가하였다. 또한, UCC의 건설과 운영에 필요한 전체 비용 관점에서 최적의 시나리오를 비교 선정하였다. 본 연구의 결과는 도심 내 말단 배송을 위한 유통 네트워크를 설계해야 하는 관리자 혹은 정부 기관의 담당자들이 합리적인 의사결정을 내리기 위한 객관적인 근거 자료로 활용될 수 있을 것이다.
Last-Mile delivery optimization plays a key role in the urban supply chain operation, which is the most expensive and time-consuming and most complicated part of the whole delivery process. The urban consolidation center (UCC) is regarded as a significant asset for supporting customer demand in the ...
Last-Mile delivery optimization plays a key role in the urban supply chain operation, which is the most expensive and time-consuming and most complicated part of the whole delivery process. The urban consolidation center (UCC) is regarded as a significant asset for supporting customer demand in the last-mile delivery service. It is the key benefit of UCC to improve the load balance of vehicles and to reduce the total traveling distance by finding the better route with the well-organized multi-leg vehicle journey in the urban area. This paper presents the model using multiple scenario analysis integrated with mathematical optimization techniques using Geographic Information System (GIS). The model aims to find the best solution for the distribution network consisted of DC and UCC, which is applied to the case of Ulaanbaatar Mongolia. The proposed methodology integrates two sub-models, location-allocation model and vehicle routing problem. The multiple scenarios devised by selecting locations of UCC are compared considering the general performance and delivery patterns together. It has been adopted to make better decisions the quantitative metrics such as the economic value of capital cost, operating cost, and balance of using available resources. The result of this research may help the manager or public authorities who should design the distribution network for the last mile delivery service optimization using UCC within the urban area.
Last-Mile delivery optimization plays a key role in the urban supply chain operation, which is the most expensive and time-consuming and most complicated part of the whole delivery process. The urban consolidation center (UCC) is regarded as a significant asset for supporting customer demand in the last-mile delivery service. It is the key benefit of UCC to improve the load balance of vehicles and to reduce the total traveling distance by finding the better route with the well-organized multi-leg vehicle journey in the urban area. This paper presents the model using multiple scenario analysis integrated with mathematical optimization techniques using Geographic Information System (GIS). The model aims to find the best solution for the distribution network consisted of DC and UCC, which is applied to the case of Ulaanbaatar Mongolia. The proposed methodology integrates two sub-models, location-allocation model and vehicle routing problem. The multiple scenarios devised by selecting locations of UCC are compared considering the general performance and delivery patterns together. It has been adopted to make better decisions the quantitative metrics such as the economic value of capital cost, operating cost, and balance of using available resources. The result of this research may help the manager or public authorities who should design the distribution network for the last mile delivery service optimization using UCC within the urban area.
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문제 정의
The objective of this research was to identify the optimal number and location of UCC to support the demand of retailers. In Table 4, it has been described and outlined the ten possible scenarios.
The remainder, the conclusion of this summary of multiple scenario results show that worst three scenarios are 2, 10, and 9 and the best three scenarios are 3, 4, and 5. The result of this research may come from help the manager or public authorities who should design the distribution network for the last mile delivery service optimization using UCC within urban area.
However, the most of previous research have focused on designing optimal network structure with minimum number and optimal locations of logistics facilities considering only demand or route for delivery from the distribution centers. Therefore, in this study, it has been presented a framework to design the supply chain network, which can minimize the total cost for building UCC and operating the distribution with the practical conditions for delivery. To find the optimal distributing network, it has been integrated the Locating-routing problem (LRP) with Location-allocation problem (LAP) and vehicle routing problem (VRP).
제안 방법
We compared the performance of several scenarios with multiple UCC and it is possible to make better decision to design the distribution network using UCC. In details, we presented the various quantitative performance indicators to compare ten different scenarios such as the total traveling time, total traveling distance, number of required trucks, minimum number of UCC, and fairness among drivers based on the practical demand and traveling routes.
In this research, it has been focused on finding the minimum number of optimal locations of facilities while supporting the demand from the delivery points and minimizing the total cost which consists with the initial investment and operating cost. It has been reported that the logistic and transport cost contributes for about 30 percent of the price of goods[4].
In this research, we have suggested the scenario analysis for designing optimal distribution network. The framework of this research has integrated the well-known mathematical optimization problems and then analyzed to find the best solution using UCC. In details, the proposed methodology, Locating-routing problem, integrated LAP and VRP.
Also, the searching algorithm has been applied to optimize the location of UCC; to determine different type of fleet vehicles and considering optimal delivery routes from UCCs to their assigned customer. The objective of the problem is to minimize the total cost of implementing UCC and minimizing emissions based on scenarios of policies.
Second, the optimal routes are developed to visit demanding points from UCC. The performance of all scenario is compared based on the several quantitative metrics such as the number of required trucks, traveling distance and time, the number of UCC. Finally, all scenarios were compared with the total cost which consists with operating cost and initial investment for building UCC.
UCCs implementation schemes in a changed distribution pattern, especially design of distribution structure was the most common suggestion among the studies[6][7][8]. The studies described the changes in the number of vehicle trips as changed in the number of vehicle kilometers and changes in the number of vehicles. Most of studies highlighted the importance of considering selection of location.
후속연구
Also, the practical conditions such as average driving speed on different route are not available. Further research could extend this research by considering the future demand and checking the robustness of current solution using sensitive analysis.
참고문헌 (19)
Shelagh Dolan. "The Challenges of Last Mile Logistics & Delivery Technology Solutions." Business Insider Intelligence, 2018.
Taniguchi, Eiichi, and Russell G Thompson. City Logistics: Mapping the Future, CRC Press, 2015.
Browne, M., Allen, J., & Leonardi, J. "Evaluating the Use of an Urban Consolidation Centre and Electric Vehicles in Central London." IATSS Research, Vol. 35, No. 1, 1-6, 2011.
Asian Development Bank. "Breaking Barriers: Leveraging Mongolia's Transport and Logistics Sector." Manila, Philippines: Asian Development Bank, 2018.
Allen, J., Browne, M., Woodburn, A., & Leonardi, J. "A Review of Urban Consolidation Centres in the Supply Chain Based on a Case Study Approach." Supply Chain Forum: An International Journal, Vol. 15, No. 4, 100-112. 2014.
Bjorklund, M., & Johansson, H,. "Urban Consolidation Centre - a Literature Review, Categorisation, and a Future Research Agenda." International Journal of Physical Distribution & Logistics Management, Vol. 48, No. 8, 745-64. 2018.
Sweet, M., Woodburn, A.G. and Allen, J., and Browne Michael. "Urban Freight Consolidation Centres." Project report. 1: University of Westminster, Transport Studies Group, November 2, 2005.
Simoni, Michele D., Pavle Bujanovic, Stephen D. Boyles, and Erhan Kutanoglu. "Urban Consolidation Solutions for Parcel Delivery Considering Location, Fleet and Route Choice." Case Studies on Transport Policy, Vol. 6, No. 1, 112-24. 2018.
Juthathip, S. "Urban Transportation Network Drsign for Cold Chain Using GIS the Case of Bangkok." Graduate School of Logistic, Incheon National University, 2019.
Ooluun, V. "Mongolian Milk from Herder's Farm to Your Home." Montsame. No. 20, 2017.
van Heeswijk, W., Larsen, R., & Larsen, A. "An Urban Consolidation Center in the City of Copenhagen: A Simulation Study." International Journal of Sustainable Transportation, Vol.13, No. 9, 675-91. 2019.
Van Duin, J. R., Quak, H., & Munuzuri, J. "New challenges for urban consolidation centres: A case study in The Hague." Procedia-Social and Behavioral Sciences, Vol. 2, No.3, 6177-6188. 2010.
Janjevic, M., Lebeau, P., Ndiaye, A. B., Macharis, C., Van Mierlo, J., & Nsamzinshuti, A., "Strategic Scenarios for Sustainable Urban Distribution in the Brussels-Capital Region Using Urban Consolidation Centres." Transportation Research Procedia, No.12, 598-612. 2016.
Duin, J.H.R. van, T. van Dam, B. Wiegmans, & L.A. Tavasszy. "Understanding Financial Viability of Urban Consolidation Centres: Regent Street (London), Bristol/Bath & Nijmegen." Transportation Research Procedia, No.16, 61-80, 2016.
Scott W., Scott W. "Freight Consolidation Centre Study", South East Scotland Transport Partnership, 2010.
Murray, Alan T., Jing Xu, Zifan Wang, and Richard L. Church. "Commercial GIS Location Analytics: Capabilities and Performance." International Journal of Geographical Information Science, Vol. 33, No. 5, 1106-30. 2019.
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