공컨테이너관리 기법을 활용한 효율적인 컨테이너 공급망

학위논문 (박사) -- 서울대학교 대학원 : 공과대학 산업공학과, 2021. 2. 문일경.Due to a remarkable surge in global trade volumes led by maritime transportation, shipping companies should make a great effort in managing their container flows especially in case of carrier-owned containers. To do so, they comprehensively implement empty container management strategies and accelerate the flows in a cost- and time-efficient manner to minimize total relevant costs while serving the maximal level of customers demands. However, many critical issues in container flows universally exist due to high uncertainty in reality and hinder the establishment of an efficient container supply chain. In this dissertation, we fully discuss such issues and provide mathematical models along with specific solution procedures. Three types of container supply chain are presented in the following: (i) a two-way four-echelon container supply chain; (ii) a laden and empty container supply chain under decentralized and centralized policies; (iii) a reliable container supply chain under disruption. These models explicitly deal with high risks embedded in a container supply chain and their computational experiments offer underlying managerial insights for the management in shipping companies. For (i), we study empty container management strategy in a two-way four-echelon container supply chain for bilateral trade between two countries. The strategy reduces high maritime transportation costs and long delivery times due to transshipment. The impact of direct shipping is investigated to determine the number of empty containers to be repositioned among selected ports, number of leased containers, and route selection to satisfy the demands for empty and laden containers for exporters and importers in two regions. A hybrid solution procedure based on accelerated particle swarm optimization and heuristic is presented, and corresponding results are compared. For (ii), we introduce the laden and empty container supply chain model based on three scenarios that differ with regard to tardiness in the return of empty containers and the decision process for the imposition of fees with the goal of determining optimal devanning times. The effectiveness of each type of policy - centralized versus decentralized - is determined through computational experiments that produce key performance measures including the on-time return ratio. Useful managerial insights on the implementation of these polices are derived from the results of sensitivity analyses and comparative studies. For (iii), we develop a reliability model based on container network flow while also taking into account expected transportation costs, including street-turn and empty container repositioning costs, in case of arc- and node-failures. Sensitivity analyses were conducted to analyze the impact of disruption on container supply chain networks, and a benchmark model was used to determine disruption costs. More importantly, some managerial insights on how to establish and maintain a reliable container network flow are also provided.해상 수송이 주도함으로써 전 세계 무역량이 급증하기 때문에 회사 소유 컨테이너는 컨테이너 흐름을 관리하는 데 많은 노력을 기울여야 한다. 이를 위해 공 컨테이너 관리 전략을 포괄적으로 구현하고 효율적인 수송 비용 및 시간 절감 방식으로 컨테이너 흐름을 원활히 하여 관련 총비용을 최소화하는 동시에 고객의 수요를 최대한 충족하게 된다. 그러나 현실에서는 높은 불확실성 때문에 컨테이너 흐름에 대한 많은 주요한 이슈가 보편적으로 존재하고 효율적인 컨테이너 공급망 구축을 방해한다. 본 논문에서는 이러한 이슈에 대해 전반적으로 논의하고 적절한 해법과 함께 수리 모형을 제공한다. 이를 위해 세 가지 유형의 컨테이너 공급망을 다룬다. 먼저 (i) 양방향 네 단계 컨테이너 공급망, (ii) 분권화 및 중앙 집중화 정책에 따른 적∙공 컨테이너 공급망; 그리고 (iii) disruption 상황 속에서 신뢰성을 고려하는 컨테이너 공급망이다. 본 논문에서 제시한 세 가지 모형은 컨테이너 공급망에 내재 된 높은 위험을 직접 다루며 계산 실험은 해운 회사의 경영진이나 관계자를 위해 주요한 관리 인사이트를 제공한다. (i)의 경우, 두 지역 간 양자 무역을 위한 양방향 네 단계 컨테이너 공급망에서 공 컨테이너 관리 전략을 연구한다. 이 전략은 환적으로 인한 높은 해상 운송 비용과 긴 배송 시간을 줄일 수 있다. 또한, 직항 수송의 영향을 조사하여 선택된 항구 중 재배치 할 공 컨테이너 수, 임대 컨테이너 수, 두 지역의 수출업자와 수입업자의 적∙공 컨테이너 대한 수요를 만족하기 위한 경로 선택을 결정하게 된다. APSO 및 휴리스틱을 기반으로 하는 하이브리드 해법을 제시하며 비교 실험을 하였다. (ii)의 경우 최적 devanning time 결정을 목표로 공 컨테이너의 반환 지연과 해당 수수료 부과 결정 프로세스와 관련하여 서로 다른 세 가지 시나리오를 기반으로 적∙공 컨테이너 공급망 모형을 제시한다. 각 유형의 정책적(분권화 및 중앙 집중화) 효과는 정시 반환율을 포함한 주요 성능 측정을 고려하는 계산 실험을 통해 결정된다. 이러한 정책 실행에 대한 유용한 관리 인사이트는 민감도 분석 및 비교 연구의 결과에서 도출한다. (iii)의 경우, 본 논문은 컨테이너 네트워크 흐름을 기반으로 하는 신뢰성 모형을 개발하는 동시에 아크 및 노드 failure가 있을 때 street-turn 및 공 컨테이너 재배치 비용을 포함한 기대 총 비용을 구한다. 중단이 컨테이너 공급망 네트워크에 미치는 영향을 분석하기 위해 민감도 분석을 수행했으며 disruption 비용을 결정하기 위해 벤치마크 모형을 활용한다. 더불어 신뢰성을 고려한 컨테이너 네트워크 흐름을 구축하고 신뢰성을 유지하는 방법에 대한 관리적 인사이트도 제공한다.Abstract i Contents ii List of Tables vi List of Figures viii 1. Introduction 1 1.1 Empty Container Repositioning Problem 1 1.2 Reliability Problem 3 1.3 Research Motivation and Contributions 4 1.4 Outline of the Dissertation 7 2. Two-Way Four-Echelon Container Supply Chain 8 2.1 Problem Description and Literature Review 8 2.2 Mathematical Model for the TFESC 15 2.2.1 Overview and Assumptions 15 2.2.2 Notation and Formulation 19 2.3 Solution Procedure for the TFESC 25 2.3.1 Pseudo-Function-based Optimization Problem 25 2.3.2 Objective Function Evaluation 28 2.3.3 Heuristics for Reducing the Number of Leased Containers 32 2.3.4 Accelerated Particle Swarm Optimization 34 2.4 Computational Experiments 37 2.4.1 Heuristic Performances 39 2.4.2 Senstivity Analysis of Varying Periods 42 2.4.3 Senstivity Analysis of Varying Number of Echelons 45 2.5 Summary 48 3. Laden and Empty Container Supply Chain under Decentralized and Centralized Policies 50 3.1 Problem Description and Literature Review 50 3.2 Scenario-based Model for the LESC-DC 57 3.3 Model Development for the LESC-DC 61 3.3.1 Centralized Policy 65 3.3.2 Decentralized Policies (Policies I and II) 67 3.4 Computational Experiments 70 3.4.1 Numerical Exmpale 70 3.4.2 Sensitivity Analysis of Varying Degree of Risk in Container Return 72 3.4.3 Sensitivity Analysis of Increasing L_0 74 3.4.4 Sensitivity Analysis of Increasing t_r 76 3.4.5 Sensitivity Analysis of Decreasing es and Increasing e_f 77 3.4.6 Sensitivity Analysis of Discounting 〖pn〗_{f1} and 〖pn〗_{f2} 78 3.4.7 Sensitivity Analysis of Different Container Fleet Sizes 79 3.5 Managerial Insights 81 3.6 Summary 83 4. Reliable Container Supply Chain under Disruption 84 4.1 Problem Description and Literature Review 84 4.2 Mathematical Model for the RCNF 90 4.3 Reliability Model under Disruption 95 4.3.1 Designing the Patterns of q and s 95 4.3.2 Objective Function for the RCNF Model 98 4.4 Computational Experiments 103 4.4.1 Sensitivity Analysis of Expected Failure Costs 106 4.4.2 Sensitivity Analysis of Different Network Structures 109 4.4.3 Sensitivity Analysis of Demand-Supply Variation 112 4.4.4 Managerial Insights 115 4.5 Summary 116 5. Conclusions and Future Research 117 Appendices 120 A Proof of Proposition 3.1 121 B Proof of Proposition 3.2 124 C Proof of Proposition 3.3 126 D Sensitivity Analyses for Results 129 E Data for Sensitivity Analyses 142 Bibliography 146 국문초록 157 감사의 글 160Docto

The design of effective and robust supply chain networks

Tableau d’honneur de la Faculté des études supérieures et postdoctorales, 2009-2010Pour faire face aux risques associés aux aléas des opérations normales et aux périls qui menacent les ressources d'un réseau logistique, une méthodologie générique pour le design de réseaux logistiques efficaces et robustes en univers incertain est développée dans cette thèse. Cette méthodologie a pour objectif de proposer une structure de réseau qui assure, de façon durable, la création de valeur pour l'entreprise pour faire face aux aléas et se prémunir contre les risques de ruptures catastrophiques. La méthodologie s'appuie sur le cadre de prise de décision distribué de Schneeweiss et l'approche de modélisation mathématique qui y est associée intègre des éléments de programmation stochastique, d'analyse de risque et de programmation robuste. Trois types d'événements sont définis pour caractériser l'environnement des réseaux logistiques: des événements aléatoires (ex. la demande, les coûts et les taux de changes), des événements hasardeux (ex. les grèves, les discontinuités d'approvisionnement des fournisseurs et les catastrophes naturelles) et des événements profondément incertains (ex. les actes de sabotage, les attentats et les instabilités politiques). La méthodologie considère que l'environnement futur de l'entreprise est anticipé à l'aide de scénarios, générés partiellement par une méthode Monte-Carlo. Cette méthode fait partie de l'approche de solution et permet de générer des replications d'échantillons de petites tailles et de grands échantillons. Elle aide aussi à tenir compte de l'attitude au risque du décideur. L'approche générique de solution du modèle s'appuie sur ces échantillons de scénarios pour générer des designs alternatifs et sur une approche multicritère pour l'évaluation de ces designs. Afin de valider les concepts méthodologiques introduits dans cette thèse, le problème hiérarchique de localisation d'entrepôts et de transport est modélisé comme un programme stochastique avec recours. Premièrement, un modèle incluant une demande aléatoire est utilisé pour valider en partie la modélisation mathématique du problème et étudier, à travers plusieurs anticipations approximatives, la solvabilité du modèle de design. Une approche de solution heuristique est proposée pour ce modèle afin de résoudre des problèmes de taille réelle. Deuxièmement, un modèle incluant les aléas et les périls est utilisé pour valider l'analyse de risque, les stratégies de resilience et l'approche de solution générique. Plusieurs construits mathématiques sont ajoutés au modèle de base afin de refléter différentes stratégies de resilience et proposer un modèle de décision sous risque incluant l'attitude du décideur face aux événements extrêmes. Les nombreuses expérimentations effectuées, avec les données d'un cas réaliste, nous ont permis de tester les concepts proposés dans cette thèse et d'élaborer une méthode de réduction de complexité pour le modèle générique de design sans compromettre la qualité des solutions associées. Les résultats obtenus par ces expérimentations ont pu confirmer la supériorité des designs obtenus en appliquant la méthodologie proposée en termes d'efficacité et de robustesse par rapport à des solutions produites par des approches déterministes ou des modèles simplifiés proposés dans la littérature

A Bi-Objective Programming Model for Reliable Supply Chain Network Design Under Facility Disruption

Supply chain networks generally are composed of four main entity types: supplier, production centers, distribution centers and demand zones that consist of facilities whose activities involve the transformation of raw material into finished products that are later delivered from the suppliers to the end customers. Supply chain network design as the most important strategic decision in supply chain management plays an important role in the overall environmental and economic performance of the supply chain. The nature and complexity of today’s supply chains network make them vulnerable to various risks. One of the most important risks is disruption risk. Disruptions are costly and can be caused by internal or external sources to the supply chain, thus it is crucial that managers take appropriate measures of responses to reduce its negative effects. A recovery time of disrupted facilities and return it to the normal condition can be an important factor for members of the supply chain. In this paper, a bi-objective model is developed for reliable supply chain network design under facility disruption. To solve this model, we have applied two approaches, i.e., ε constraint method as an exact method and non- dominated sorting genetic algorithm (NSGAII) as a meta-heuristic method

Disruptions in Supply Chain Transportation: A literature review

Efficient and well-organised transportation is crucial to the success of any supply chain operation, but disruptions can occur in competitive and globalised environments, leading to potential damage and interruptions. A thorough literature review on supply chain transportation research is conducted to address these disruptions from a transportation perspective. The objective is to present recent research on various aspects of the transportation problems, address the gap considering disruptions and propose a framework that outlines the factors that may cause transportation disruptions, their relationships, the types of impacts they have, and how they depend on one another

Design and Analysis of Efficient Freight Transportation Networks in a Collaborative Logistics Environment

The increase in total freight volumes, reducing volume per freight unit, and delivery deadlines have increased the burden on freight transportation systems of today. With the evolution of freight demand trends, there also needs to be an evolution in the freight distribution processes. Today\u27s freight transportation processes have a lot of inefficiencies that could be streamlined, thus preventing concerns like increased operational costs, road congestion, and environmental degradation. Collaborative logistics is one of the approaches where supply chain partners collaborate horizontally or/and vertically to create a centralized network that is more efficient and serves towards a common goal or objective. In this dissertation, we study intermodal transportation, and cross-docking, two major pillars of efficient, cheap, and faster freight transportation in a collaborative environment. We design an intermodal network from a centralized network perspective where all the participants intermodal operators, shippers, carriers, and customers strive towards a synchronized and cost-efficient freight network. Also, a cross-dock scheduling problem is presented for competitive shippers using a centralized cross-dock facility. The problem develops a fast heuristic and meta-heuristic approach to solve large-scale real-world problems and draws key insights from a cross-dock operator and inbound carrier\u27s perspectives

Architecting Fail-Safe Supply Chains / Networks

Disruptions are large-scale stochastic events that rarely happen but have a major effect on supply networks’ topology. Some examples include: air traffic being suspended due to weather or terrorism, labor unions strike, sanctions imposed or lifted, company mergers, etc. Variations are small-scale stochastic events that frequently happen but only have a trivial effect on the efficiency of flow planning in supply networks. Some examples include: fluctuations in market demands (e.g. demand is always stochastic in competitive markets) and performance of production facilities (e.g. there is not any perfect production system in reality). A fail-safe supply network is one that mitigates the impact of variations and disruptions and provides an acceptable level of service. This is achieved by keeping connectivity in its topology against disruptions (structurally fail-safe) and coordinating the flow through the facilities against variations (operationally fail-safe). In this talk, I will show that to have a structurally fail-safe supply network, its topology should be robust against disruptions by positioning mitigation strategies and be resilient in executing these strategies. Considering “Flexibility” as a risk mitigation strategy, I answer the question “What are the best flexibility levels and flexibility speeds for facilities in structurally fail-safe supply networks?” Also, I will show that to have an operationally fail-safe supply network, its flow dynamics should be reliable against demand- and supply-side variations. In the presence of these variations, I answer the question “What is the most profitable flow dynamics throughout a supply network that is reliable against variations?” The method is verified using data from an engine maker. Findings include: i) there is a tradeoff between robustness and resilience in profit-based supply networks; ii) this tradeoff is more stable in larger supply networks with higher product supply quantities; and iii) supply networks with higher reliability in their flow planning require more flexibilities to be robust. Finally, I will touch upon possible extensions of the work into non-profit relief networks for disaster management

Intelligent logistics: Involving the customer

The role of logistics in effective supply chain management is increasingly critical, and researchers and practitioners have recently focused their attention in designing more intelligent systems to address today’s challenges. In this paper, we focus on one such challenge concerning improving the role of the customer in logistics operations. In particular, we identify specific developments in the systems governing core logistics operations, which will enhance the customer experience. This paper proposes a conceptual model for customer orientation in intelligent logistics and describes a number of specific developments the authors are involved in.This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.compind.2015.10.00