On-Demand Pooling Strategy for Foldable Containers in Empty Container Repositioning = 공컨테이너재배치 문제에서의접이식컨테이너온디맨드 풀링 전략

국문 초록 (Abstract)

본연구는 접이식컨테이너를 활용한중립적온디맨드 풀링 서비스내에서렌탈 기반
운영및공컨테이너재배치(ECR) 전략을탐구한다. 조달, 다기간재배치, 재고관리,
단기 렌탈을운영제약조건하에서동시에 다루는 혼합정수최적화모델을제안하며,
다양한실행방안을수용하기 위한실용적정책 변형모델도함께 제시한다. 대표적인
다지역 네트워크를 대상으로한수치 실험을통해다양한롤아웃및정책 시나리오를
분석하고, 주요파라미터에 대한민감도분석을수행하였다. 실험결과, 렌탈 풀링은총
비용절감, 부족위험최소화, 재고증폭완화를 통해운영성과를 향상시키는 것으로
나타났다. 이러한효과는 수요변동성이높거나 초기 재고가제한적인조건에서특히
두드러지게나타났다.

다국어 초록 (Multilingual Abstract)

This paper explores strategies for rental-enabled operations and empty container
repositioning (ECR) within a neutral, on-demand pooling service that utilizes fold-
able containers. We propose mixed-integer optimization models to simultaneously
address procurement, multi-period repositioning, inventory management, and short-
term rentals, all while adhering to operational constraints. Additionally, we introduce
practical policy variants to accommodate different implementation choices. Through
computational experiments on representative multi-region networks, we analyze var-
ious rollout and policy scenarios, considering targeted sensitivity analyses. The re-
sults demonstrate that pooling with rentals enhances operational performance by
reducing total costs, minimizing shortage risks, and mitigating inventory amplifica-
tion. These benefits are particularly pronounced under volatile demand or limited
initial inventory conditions.

목차 (Table of Contents)

• Abstract i
• Contents v
• List of Tables vi
• List of Figures viii
• Chapter 1 Introduction 1
• 1.1 1.2 1.3 Problem Description 1
• Research Motivation and Contribution 7
• Organization of the Thesis8
• Chapter 2 Literature Review 9
• 2.1 2.2 Empty Container Repositioning (ECR) 9
• 2.1.1 Early Modeling Studies (1993-2009) 9
• 2.1.2 Policy and Strategy Development (2010-2014) 10
• 2.1.3 Recent Advances (2020-2025) 10
• Foldable Container Innovation 11
• 2.2.1 Concept Introduction and Feasibility (2001-2012) 11
• 2.2.2 Operational Optimization (2013-2020) 11
• iii
• 2.3 2.4 2.2.3 Recent Applications and Extensions (2021-2024) 12
• Pallet Pooling 12
• Research Gap Analysis 13
• Chapter 3 Solution Approaches 16
• 3.1 3.2 3.3 3.4 3.5 Problem Assumptions 16
• Mathematical Formulation 17
• 3.2.1 Sets and Parameters 17
• 3.2.2 Decision Variables 18
• Objective Function 20
• Model Constraints 20
• 3.4.1 Inventory Balance Constraints 20
• 3.4.2 Demand Satisfaction Constraints 20
• 3.4.3 Rental Capacity Constraints 21
• 3.4.4 Folding and Unfolding Constraints 21
• 3.4.5 Additional Constraints 22
• Operator Performance Evaluation 23
• 3.5.1 Additional Operator Parameters23
• 3.5.2 Solution-Based Quantities 23
• 3.5.3 Performance Indicators24
• Chapter 4 Computational Experiments 25
• 4.1 Experimental Setup .25
• 4.1.1 Description of Test Instances 26
• 4.1.2 Baseline Results 29
• 4.1.3 Total Cost vs. Initial Inventory 30
• 4.1.4 Cost-Effectiveness Crossover 30
• 4.1.5 Expanded Scenarios: Ramp Adoption Strategies 39
• 4.1.6 Overcoming Adoption Barriers: The Role of Neutral Operator 45
• 4.1.7 Managerial Insights 50
• Chapter 5 Conclusion 54
• 5.1 5.2 5.3 Summary and Key Findings 54
• 5.1.1 Inventory-Dependent Strategy Optimization 54
• 5.1.2 The 10.8:1 Leverage Effect 55
• 5.1.3 Strategic Network Deployment and Pricing Robustness 55
• Limitations and Future Research 56
• Concluding Remarks 57
• Bibliography 59
• 국문초록 65
• 감사의 글 66