Article
Engineering, Industrial
Seyedmohsen Hosseini, Dmitry Ivanov
Summary: The study introduces a method of modeling and quantifying supply chain disruption impacts in the pandemic using a multi-layer Bayesian network model, combining resilience and viability perspectives to explicitly account for pandemic settings. The research results can serve as a decision-support tool for predicting and better understanding the pandemic impacts on supply chain performance.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Editorial Material
Engineering, Industrial
Alexandre Dolgui, Dmitry Ivanov
Summary: The ripple effect is a specific area in supply chains that has a strong impact on supply chain resilience. Research shows how disruptive events spread through the supply chain and affect its resilience and performance. In recent years, research on ripple effect management, modeling, and assessment has gained significant interest.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Management
D. G. Mogale, Xun Wang, Emrah Demir, Vasco Sanchez Rodrigues
Summary: This study aims to model and quantitatively analyze a range of SC disruption risks affecting a UK online retailer in response to the increased vulnerability caused by globalization, competitiveness, and uncertainties. The study found that the retailer experienced multiple disruption risks, such as demand and supply shocks, facility closures, and disruption propagation simultaneously in 2020. It also investigated the response of UK retailers to the first and second waves of the pandemic and the impact on multiple products.
OPERATIONS MANAGEMENT RESEARCH
(2023)
Article
Engineering, Industrial
Jessica Olivares-Aguila, Waguih ElMaraghy
Summary: Disruptions in the downstream levels of a supply chain have a greater impact on performance and should be given higher priority, while expediting after disruptions does not benefit long-term supply chain performance.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Review
Engineering, Industrial
Arrate Llaguno, Josefa Mula, Francisco Campuzano-Bolarin
Summary: Supply chains are becoming increasingly sophisticated and vital for competitiveness in many firms. However, their global and complex nature also makes them vulnerable to the risk of interruptions. This article systematically reviews the ripple effect in supply chains and proposes measures to mitigate its impact.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Engineering, Industrial
Xavier Brusset, Morteza Davari, Aseem Kinra, Davide La Torre
Summary: This paper discusses the ripple effects of disruptions in supply networks caused by the pandemic and proposes a model that combines logistics with an epidemiological model to predict and simulate the impact on workforce in the supply chain. The findings can provide useful insights for managers and scholars to mitigate the impact of a pandemic.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Operations Research & Management Science
Dmitry Ivanov
Summary: The COVID-19 pandemic caused havoc on supply chains, highlighting the importance of management during and after the pandemic. Unawareness of after-shock risks can lead to destabilized production-inventory dynamics and increased costs for supply chains.
ANNALS OF OPERATIONS RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Farhad Habibi, Ripon Kumar Chakrabortty, Alireza Abbasi
Summary: In the face of disruptions in global supply chains, a comprehensive framework for evaluating supply chain resilience is crucial. Existing techniques have limitations and fail to consider the ripple effect, resulting in biased assessments. This study proposes a comprehensive evaluation scheme that introduces six metrics to assess different capacities of resilience and validates its applicability on real-world supply chain networks.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Engineering, Industrial
Tadeusz Sawik
Summary: “This paper presents a novel quantitative approach and stochastic quadratic optimisation model to maintain supply chain viability under the ripple effect. Instead of viability kernel commonly used in the viability theory, this paper establishes the boundaries on acceptable production states for which the production can be continued under the ripple effect, with no severe losses. The findings indicate that for the extreme values of the weight factor, the viable production trajectory is inclined toward the corresponding boundary trajectory and remains in-between the two boundaries, when both objectives are equally important. Keeping production trajectory in-between the two boundaries makes the supply chain more resilient to disruption risks, while the supply chain resilience diminishes as the production trajectory approaches a boundary trajectory. Then a more severe disruption may push the production outside the viability region and cause greater losses.”
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Ming Liu, Tao Lin, Feng Chu, Yueyu Ding, Feifeng Zheng, Chengbin Chu
Summary: In practice, supplier actions are taken to reduce the impact of disruption propagation and ensure material flow continuity. The selection of appropriate supplier actions to minimize disruption risk is of interest. This study investigates a new problem in supply chain management, considering supplier actions, and proposes an integrated approach to address it efficiently.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2023)
Article
Engineering, Chemical
Milena Kajba, Borut Jereb, Matevz Obrecht
Summary: This paper explores the application of Digital Twin technology to supply chain systems and other logistics IT trends, aiming to research the pressing issue of ensuring the visibility and resilience of future supply chain systems. The objective of the paper is to produce a conceptual model for the investment assessment of necessary IT resources. The paper establishes the relevance of logistics IT trends to supply chain systems and proposes Digital Twin technology applications to other logistics IT trends.
Article
Engineering, Industrial
Vinod Kumar Chauhan, Supun Perera, Alexandra Brintrup
Summary: Research has shown that supply networks are more robust under random disruptions, but more vulnerable to hub disruptions under cascade conditions. In contrast, nested structures are less resilient as they do not benefit from a response strategy where buyers seek alternative suppliers.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Operations Research & Management Science
Dmitry Ivanov
Summary: This study uses simulation analysis to examine the impacts of blackouts on supply chains, considering SC performance, resilience, and viability. The results reveal that blackouts are a special case of SC risks characterized by simultaneous shutdown of processes, disruption propagations, and the danger of viability losses. Simulation experiments show that factors such as power loss propagation, blackout duration, unavailability of supply and logistics, and unpredictable customer behavior determine the blackout impact and recovery strategies. The findings can aid decision-makers in predicting the operational and long-term impacts of blackouts on SCs and developing mitigation and recovery strategies.
ANNALS OF OPERATIONS RESEARCH
(2022)
Review
Operations Research & Management Science
K. Katsaliaki, P. Galetsi, S. Kumar
Summary: This study reviews important literature on supply chain disruptions, analyzing the impact of disruptions, recovery strategies, modeling approaches, and IT tools. Additionally, a future research agenda is proposed to address research gaps in the field of supply chain disruptions.
ANNALS OF OPERATIONS RESEARCH
(2021)
Article
Engineering, Industrial
Selmen Boubaker, Zied Jemai, Evren Sahin, Yves Dallery
Summary: This paper proposes a quantitative approach to evaluate and improve supply chain agility and develops a model to simulate the flow of information and physical goods in different situations. A numerical study is presented and interesting insights from real-life applications are discussed.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Shuzhen Chen, Yuchen Pan, Desheng Wu, Alexandre Dolgui
Summary: This paper develops a game model to analyze the long-term collection strategies in a closed-loop supply chain with a manufacturer, a remanufacturer, and a retailer. The results show that the manufacturer can develop the remanufacturing technology quickly and achieve higher profits under certain conditions. The choice between direct and indirect reverse channels depends on the entry barrier and cost advantage.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
G. Castane, A. Dolgui, N. Kousi, B. Meyers, S. Thevenin, E. Vyhmeister, P-O Ostberg
Summary: This paper outlines the main idea and approach of the H2020 ASSISTANT project, which aims to investigate AI-based tools for adaptive manufacturing environments and focuses on developing digital twins for integration with production planning and control.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Dan Luo, Simon Thevenin, Alexandre Dolgui
Summary: This paper discusses the impact of Industry 4.0 on production planning approaches and software. A digital twin framework is proposed to integrate production planning systems and frontier technologies. The application and benefits of technologies such as the internet of things, cloud manufacturing, blockchain, and big data analytics in production planning are analyzed. Future research and application directions in production planning are also discussed.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Arsalan Yousefloo, Reza Babazadeh, Mehrdad Mohammadi, Amir Pirayesh, Alexandre Dolgui
Summary: This paper proposes a multi-objective scenario-based robust stochastic optimization model for designing a sustainable Municipal Solid Waste (MSW) management network. The model considers the dynamic factors influencing MSW management network and integrates sustainability indicators to achieve a balance between quantitative and qualitative evaluation. Additionally, the model investigates waste treatment technologies and emphasizes the importance of fuel consumption on transportation costs and CO2 emissions.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Computer Science, Interdisciplinary Applications
Paula Metzker, Simon Thevenin, Yossiri Adulyasak, Alexandre Dolgui
Summary: This paper addresses the lot-sizing problem under yield uncertainty using a robust optimization methodology. A multi-period, single-item lot-sizing problem with backorder and yield uncertainty is proposed and a robust model is formulated under a budgeted uncertainty set. The structure of the optimal lot-sizing solution is analyzed and optimal robust policies are derived. Computational experiments demonstrate the robustness and effectiveness of the proposed model, showing its ability to immunize the system against uncertainty and balance costs better compared to other models.
COMPUTERS & OPERATIONS RESEARCH
(2023)
Article
Engineering, Industrial
S. Ehsan Hashemi-Petroodi, Simon Thevenin, Sergey Kovalev, Alexandre Dolgui
Summary: This study focuses on a reconfigurable mixed-model assembly line, where tasks can be dynamically assigned to stations at each takt and workers can move among stations at the end of each takt. The order of entering product models is infinite and unknown. By modeling dynamic task assignment and workers' movements as a Markov Decision Process (MDP) and a Linear Program (LP), respectively, the line design problem is formulated as a Mixed-Integer Linear Program (MILP) that integrates the MDP model. Reduction rules and a decomposed transition process are proposed to simplify the model. The proposed MDP models demonstrate superior performance compared to the model-dependent and fixed assignments usually studied in the literature.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2023)
Article
Engineering, Industrial
Behdin Vahedi-Nouri, Reza Tavakkoli-Moghaddam, Zdenek Hanzalek, Alexandre Dolgui
Summary: This paper explores an integrated production scheduling and workforce planning problem in a Reconfigurable Manufacturing System (RMS) using reconfigurable machines and human-robot collaboration. A new Mixed-Integer Linear Programming (MILP) model and an efficient Constraint Programming (CP) model are developed to solve the problem. Computational experiments show the superiority of the CP model over the MILP model in smaller instances and its ability to find high-quality solutions for larger instances within a reasonable computation time. It provides recommendations for managers dealing with this complex problem.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
David Tremblet, Abdelkrim R. Yelles-Chaouche, Evgeny Gurevsky, Nadjib Brahimi, Alexandre Dolgui
Summary: This paper focuses on the multi-model assembly line balancing problem in a reconfigurable environment. The objective is to design a line configuration for each product while minimizing the maximum number of task reassignments. A mixed-integer linear program is formulated to solve this NP-hard problem. Two heuristics, a constructive one and a MILP-based one, are developed for larger instances. Experimental results demonstrate the superiority of the Halt-and-Fix heuristic in terms of solution quality and CPU time compared to the other approaches.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
Article
Economics
Olga Battaia, Alexandre Dolgui, Nikolai Guschinsky, Mikhail Y. Kovalyov
Summary: Currently, there is strong political support for reducing carbon emissions in the transportation sector globally. Public transport operators are embracing electric buses as a means to decrease greenhouse gas emissions and improve air quality. However, the use of electric buses requires a well-functioning urban charging infrastructure. This study focuses on optimizing the design of such an infrastructure to maximize the passenger capacity of electric buses.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2023)
Article
Computer Science, Interdisciplinary Applications
Olga Battaia, Alexandre Dolgui, Nikolai Guschinsky, Boris Rozin
Summary: Reducing greenhouse gas emissions is essential for sustainable cities, and a sustainable public transportation system is considered an efficient long-term solution. This paper proposes a framework for designing a sustainable infrastructure for fast-charging electric buses, which helps decision makers determine the fleet of electric buses, design charging facilities, and optimize passenger flow to minimize emissions. An efficient mixed integer linear programming model is developed for interchangeable chargers for electric buses. A case study in Minsk demonstrates the decision-making process, and extensive computer experiments show that the model outperforms existing methods in terms of efficiency.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Management
Behnam Vahdani, Mehrdad Mohammadi, Simon Thevenin, Patrick Meyer, Alexandre Dolgui
Summary: This paper addresses a multi-period production-inventory-sharing problem to overcome the challenges caused by the rapid spread of the COVID-19 virus. By introducing a new formulation and utilizing a bespoke epidemiological model and control policy, as well as an accelerated Benders decomposition-based algorithm, the authors successfully solve large-sized test problems efficiently. The proposed sharing mechanism significantly reduces the total cost of the system and unmet demand.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2023)
Article
Engineering, Industrial
Alexandre Dolgui, Oleg Gusikhin, Dmitry Ivanov, Xingyu Li, Kathryn Stecke
Summary: This study examines a network-of-networks mechanism of cross-industry adaptation in supply chains during a crisis. The findings suggest that coordinated capacity repurposing is superior to ad-hoc adaptation, and emphasize the importance of collaboration between governmental agencies, healthcare, and industry. Concrete implementation strategies are also proposed.
Article
Engineering, Industrial
Olga Battaia, Alexandre Dolgui, Nikolai Guschinsky
Summary: This study addresses the problem of equipment selection and line balancing in machining systems design. A novel mathematical model and a heuristic algorithm are proposed for an approximate solution. The experimental results demonstrate the effectiveness of the developed methods in solving large-scale industrial problems.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Milad Elyasi, Basak Altan, Ali Ekici, Okan Orsan Ozener, Ihsan Yanikoglu, Alexandre Dolgui
Summary: This paper examines the impact of the global crisis on supply chain resilience and suggests the implementation of flexible/hybrid manufacturing systems as a viable strategy. Using Vestel Electronics as a case study, the research proposes a flexible/hybrid manufacturing production setup to address uncertain demand. By employing a scenario-based approach and a heuristic algorithm based on column generation, the optimization model demonstrates effective and cost-efficient solutions.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Management
Ming Liu, Yueyu Ding, Feng Chu, Alexandre Dolgui, Feifeng Zheng
Summary: This paper investigates a problem of improving supply chain resilience and viability under severe disruptive events, where only the probability intervals of supply chain partners' states are known. A new robust optimization model combining Causal Bayesian Network and Do-calculus is proposed, and an efficient problem-specific branch-and-bound algorithm is used to solve the problem.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2023)