Optimization of the Location-Routing Problem for Emergency Response Time in Disaster Management
- 주제(키워드) Disaster response system , Location-routing problem , Meta-heuristic , Manpower allocation problem
- 발행기관 고려대학교 대학원
- 지도교수 정태수
- 발행년도 2025
- 학위수여년월 2025. 8
- 학위명 석사
- 학과 및 전공 대학원 산업경영공학과
- 세부전공 산업경영공학전공
- 원문페이지 81 p
- 실제URI http://www.dcollection.net/handler/korea/000000304981
- UCI I804:11009-000000304981
- DOI 10.23186/korea.000000304981.11009.0003087
- 본문언어 영어
초록/요약
This study proposes a novel decision-support model for disaster response operations that integrates temporary medical center location decisions with ambulance routing and healthcare manpower allocation. We developed a mathematical model that considers patient assignments, ambulance dispatching, and the staffing requirements to deliver timely medical care. The objective is to minimize rescue time for emergency and non-emergency patients while satisfying capacity and budgetary constraints under limited medical resources. Given the NP-hard nature of the temporary medical center location-routing problem with manpower allocation (TMCLRPwMA), we propose a meta-heuristic algorithm to derive near-optimal solutions for large-scale problem instances. The proposed HGA+ incorporates customized operators such as initialization, rebalancing, crossover, mutation, and local search procedures to escape local optima. The computational performance of HGA+ is validated through numerical experiments. Sensitivity analyses on additional budgets and medical resources are conducted to provide insights that support disaster managers in making informed decisions. Additionally, case studies based in Seoul City compare existing disaster management policies with our proposed approach to demonstrate its practical advantages and applicability in real-world settings. The results confirm our model’s robustness and practical applicability to real-world disaster response systems.
more목차
Abstract i
국문초록 iii
Table of Contents v
List of Tables viii
List of Figures ix
1 Introduction 1
2 Literature review 6
3 Problem description and formulation 10
3.1 Disaster response operations management 10
3.2 The mathematical programming model 12
4 Proposed heuristic algorithm 18
4.1 Algorithm description 19
4.2 Initialization 21
4.2.1 Non-emergency patients 21
4.2.2 Emergency patients 22
4.3 New generation 24
4.3.1 Rebalancing algorithm 24
4.3.2 Crossover and mutation 27
5 Computational results 29
5.1 Benchmark dataset description and parameter settings 30
5.2 Experimental results 31
5.2.1 Experiment I: Proposed model vs. Exact approach 31
5.2.2 Experiment II: Effectiveness of the rebalancing algorithm 33
5.3 Sensitivity analysis 35
5.3.1 Analysis of the relief budget ε 35
5.3.2 Analysis of the manpower of hospital staff ∑Qh 37
5.3.3 Analysis of the robustness of the model to spatial demand shifts 41
6 Case study 46
7 Conclusions 53
Appendix 55
A Hybrid Genetic Algorithm Plus 55
B Simulation method: the policy of decision under limited budget 57
C Case study locations of TMCs and hospitals in Seoul 60
Reference 62
