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도심 내 물류거점 입지선정 및 친환경 배송수단 라스트마일 배송경로 최적화

The Research on Location Selection of Urban Distribution Centers and Routes Optimization of Eco-friendly Last-mile Delivery

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주제분류경영학

초록

The domestic e-commerce business has been expanding rapidly nowadays, and a growing percentage of retail purchases are being conducted online. Accordingly, the entire express delivery market has risen quickly from 140,598 units in 2012 to 362,967 units in 2021. The number of express deliveries per capita has surged from around 2.4 in 2000 to 70.3 in 2021. As a result, the significance of the last-mile delivery market in the logistics sector is progressively growing. However, the logistics sector, which produces a significant quantity of environmental pollutants during the last-mile delivery process, has been aggressively researching environmentally friendly delivery in light of current worldwide attention to climate change and environmental challenges. In this study, a cluster-based last-mile distribution network was proposed to utilize environmentally friendly small distribution vehicles. In order to compare and analyze the methods proposed in this study, experiments were conducted to compare the methods of selecting delivery points through clustering and establishing vehicle route planning, as well as the methods of selecting delivery points and establishing vehicle route planning by solving existing facility location problems. The experimental results show that the approach proposed in this study is superior to the existing method that uses the same number of delivery points in terms of trunkline transportation distance and uniformity of vehicle travel distance distribution. This indicates that the proposed method performs better in regions where the distribution of demand locations is not uniform and the distance between facilities is relatively considerable. This study is anticipated to be utilized by logistics enterprises in the future as a decision-making guide for establishing small-scale eco-friendly distribution networks in urban centers.

Abstract

The domestic e-commerce business has been expanding rapidly nowadays, and a growing percentage of retail purchases are being conducted online. Accordingly, the entire express delivery market has risen quickly from 140,598 units in 2012 to 362,967 units in 2021. The number of express deliveries per capita has surged from around 2.4 in 2000 to 70.3 in 2021. As a result, the significance of the last-mile delivery market in the logistics sector is progressively growing. However, the logistics sector, which produces a significant quantity of environmental pollutants during the last-mile delivery process, has been aggressively researching environmentally friendly delivery in light of current worldwide attention to climate change and environmental challenges. In this study, a cluster-based last-mile distribution network was proposed to utilize environmentally friendly small distribution vehicles. In order to compare and analyze the methods proposed in this study, experiments were conducted to compare the methods of selecting delivery points through clustering and establishing vehicle route planning, as well as the methods of selecting delivery points and establishing vehicle route planning by solving existing facility location problems. The experimental results show that the approach proposed in this study is superior to the existing method that uses the same number of delivery points in terms of trunkline transportation distance and uniformity of vehicle travel distance distribution. This indicates that the proposed method performs better in regions where the distribution of demand locations is not uniform and the distance between facilities is relatively considerable. This study is anticipated to be utilized by logistics enterprises in the future as a decision-making guide for establishing small-scale eco-friendly distribution networks in urban centers.

참고문헌 (32)

  1. 국가물류통합정보센터, "년도별 생활물류실적", 국가물류통합정보센터, ~ (2022)
  2. 자동차해체재활용업협회, "연도별 평균 폐차 주기", 자동차해체재활용업협회, ~ (2021)
  3. 최저임금위원회, "2023년 최저임금 안내문", 최저임금위원회, ~ (2022)
  4. 한국의 사회동향 2020, "통계청", 통계청, ~ (2020)
  5. 국내 석유제품 주간 가격동향, "한국석유공사", 한국석유공사, ~ (2023)
  6. 한국전력공사, "전기공급약관", 한국전력공사, ~ (2023)
  7. 김재원, "클러스터링 기반의 최적 차량 운행 계획 수립을 위한 비교연구", 한국빅데이터학회 학회지, 5(1), pp.155~180 (2020), 사)한국빅데이터학회[DOI]
  8. 김진욱, "탄소배출량 절감을 위한 친환경 운송수단 도입방안 연구 – 배송용 전기자전거의 택배 활용 중심으로 -", 로지스틱스연구, 24(4), pp.9~25 (2016), 한국로지스틱스학회[DOI]
  9. 문소현, "지역 제한 P-median 모델을 이용한 서울시 주거복지센터 입지 분석 및 모델링", 대한지리학회지, 55(2), pp.197~206 (2020), 대한지리학회[DOI]
  10. 박보라, "휴리스틱 P-Median 알고리즘을 이용한 자전거주차장 최적입지선정", 대한토목학회논문집(국문), 33(5), pp.1989~1998 (2013), 대한토목학회[DOI]
  11. 박진희, "전자상거래 환경을 고려한 위계별 물류시설의 최적 입지 선정에 관한 연구 - 예측배송시스템 관점에서 -", 로지스틱스연구, 24(4), pp.41~58 (2016), 한국로지스틱스학회[DOI]
  12. 진무위, "지역물류단지 최적 입지선정을 위한 방법론 연구", 로지스틱스연구, 25(4), pp.95~106 (2017), 한국로지스틱스학회[DOI]
  13. 이인묵, "k-means 클러스터링을 활용한 교통카드데이터 기반의 대중교통 이용자 통행패턴 생성", 한국철도학회논문집, 23(3), pp.204~215 (2020), 한국철도학회[DOI]
  14. 이종학, "분기한정법 기반의 새로운 전역최적화법: Hot Spot Strategy", 한국 CDE 학회 학술발표회 논문집, pp.659~665 (2010)
  15. 임무균, "유전자 알고리듬을 이용한 운행비용 최소화 다용량 차량경로문제", 산업공학(IE interfaces), 20(2), pp.103~111 (2007), 대한산업공학회
  16. 조건, "트리 네트워크 상에서의 p-미디안 문제에 대한 효율적인 알고리즘 개발에 관한 연구", 한국경영과학회지, 29(1), pp.57~70 (2004), 한국경영과학회
  17. 홍석미, "순회 판매원 문제에서 개미 군락 시스템을 이용한 효율적인 경로 탐색", 정보과학회논문지 : 소프트웨어 및 응용, 30(10), pp.862~866 (2003), 한국정보과학회
  18. Michael, D., "A survey of variants and extensions of the location-routing problem", Eur.J.Oper.Res, 241(2), pp.283~308 (2015)
  19. Ricardo, F., "Robust branch-and-cut-and-price for the capacitated vehicle routing problem", Mathematical Programming, 106, pp.491~511 (2006)
  20. Johannes, G., "A new vehicle for urban freight? An ex-ante evaluation of electric cargo bikes in courier services", Research in Transportation Business & Management, pp.1153~1162 (2014)
  21. Jiawei, H., "Data Mining Concepts and Techniques", pp.443~495 (2011)
  22. Roberto, N., "E-bikes and E-scooters for smart logistics : environmental and economic sustainability in pro-E-bike Italian pilots", Transportation research procedia, 14, pp.2362~2371 (2016)
  23. Beatrice, O., "Multi-objective genetic algorithms for vehicle routing problem with time windows", Applied Intelligence, 24, pp.17~30 (2006)
  24. Mark, C. P. P., "An optimization model for container inventory management", Annals of Operations Research, 273, pp.433~453 (2019)
  25. Daniel, S., "The p-median problem in a changing network: the case of Barcelona", Location Science, 6(1-4), pp.383~394 (1998)
  26. Kristina, P. S., "Unsupervised K-means clustering algorithm", IEEE access, 8, pp.880716~880727 (2020)[DOI]
  27. V. W., "Two-echelon vehicle routing problems : A literature review", European Journal of Operational Research, 304(3), pp.865~886 (2023)
  28. Wai, Y. S., "An artificial bee colony algorithm for the capacitated vehicle routing problem", European Journal of Operational Research, 215(1), pp.126~135 (2011)
  29. Vincent, F. Y., "The vehicle routing problem with simultaneous pickup and delivery and occasional drivers", Expert Systems with Applications, 214(5) (2023)[DOI]
  30. Christos, V., "Guided local search and its application to the traveling salesman problem", European Journal of Operational Research, 113(2), pp.469~499 (1999)
  31. Christos, V., "Handbook of Metaheuristics", pp.321~361 (2010)
  32. Niaz, A. W., "Vehicle routing problem with deliveries and pickups : modelling issues and meta-heuristics solution approaches", International Journal of Transportation, 2(1), pp.95~110 (2014)

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