Last-Mile Delivery Route Optimization Through Collaborative Underground Logistics System
지하물류 시스템을 활용한 라스트마일 배송 경로 최적화
- 주제(키워드) 지하 물류 시스템 , Cross-Entropy 알고리즘 , 수거 및 배송 문제 , 도시 물류
- 주제(DDC) 658.5
- 발행기관 아주대학교 일반대학원
- 지도교수 신영철
- 발행년도 2026
- 학위수여년월 2026. 2
- 학위명 석사
- 학과 및 전공 일반대학원 산업공학과
- 실제URI http://www.dcollection.net/handler/ajou/000000036091
- 본문언어 영어
- 저작권 아주대학교 논문은 저작권에 의해 보호받습니다.
초록/요약
The rapid growth of the e-commerce market has significantly increased logistics volumes, leading to severe traffic congestion, delivery delays, and increased carbon emissions in urban areas. Moreover, the capacity of road-based logistics networks has already reached its physical and operational limits, intensifying the conflict between delivery performance, cost efficiency, and sustainability. To address these challenges, the underground logistics system (ULS), which utilizes subway trains, has emerged as a promising alternative to conventional road-based logistics. However, integrating the ULS with road-based logistics introduces considerable operational complexity, requiring advanced decision-making strategies. We propose a mathematical optimization model for the Collaborative Pickup and Delivery Problem with ULS(CPDP-ULS). To overcome the high computational complexity of this model, we develop a CrossEntropy based heuristic algorithm to efficiently solve the CPDP-ULS. Comparative experiments with benchmark algorithms demonstrate the superior performance of the proposed algorithm. Additionally, a case study using realistic data shows that CPDPULS achieves higher efficiency than conventional road-based logistics.
more목차
1 Introduction 1
2 Literature review 3
2.1 Previous research on underground logistics system 3
2.2 Previous research on last-mile delivery combined with other transportation modes 4
2.3 Comparison with previous studies 6
3 Problem description and mathematical model 7
3.1 Assumptions 8
3.2 Mixed-integer linear programming based mathematical optimization model 10
4 Solution procedure 13
4.1 Basic procedure of CE algorithm 14
4.2 Cross-entropy based station allocation and pickup and delivery algorithm 17
4.2.1 Initialization 17
4.2.2 Sampling 17
4.2.3 Elite sampling 19
4.2.4 Smoothed updating 20
4.2.5 Convergence and early termination 20
5 Computational experiments 20
5.1 Performance evaluation of CE-SAPDA 21
5.1.1 Comparison with mathematical model and benchmark heuristic algorithms 21
5.1.2 Comparison with ACO algorithm 23
5.2 Realistic data based case study 24
5.2.1 Comparison between CPDP-ULS and traditional roadbased delivery 28
5.2.2 Appropriate combination of subway stations 32
5.2.3 Sensitivity analysis of travel cost 36
5.2.4 Sensitivity analysis of available unloading time at station 37
5.3 Practical insights 37
6 Conclusions 38
참고문헌 40
Appendix 46
