Article
Computer Science, Interdisciplinary Applications
Seyed Mohammad Gholami-Zanjani, Mohammad Saeed Jabalameli, Mir Saman Pishvaee
Summary: A novel bi-objective stochastic model is developed in this research for meat inventory planning, with two resiliency strategies embedded. The results indicate that resilient solutions can improve network performance and are sensitive to throughput capacity and lead-time. Trade-off interactions between the objectives provide managerial insights.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Engineering, Industrial
Jafar Namdar, S. Ali Torabi, Navid Sahebjamnia, Ninad Nilkanth Pradhan
Summary: This paper proposes a novel framework for designing a resilient supply chain network to address operational and disruption risks. The framework includes quantifying the resilience score of facilities, identifying critical processes and business continuity metrics, and designing a multi-echelon, multi-product supply chain network model. The model aims to incorporate risk attitudes into the design process and provides useful managerial insights through sensitivity analyses on hypothetical disruptions and risk attitudes.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Operations Research & Management Science
Joao Pires Ribeiro, Ana Paula F. D. Barbosa-Povoa
Summary: Supply Chain Management is constantly evolving, and Supply Chain Resilience (SCR) is a recent concept that has emerged from changes in business practices. However, there is still limited research on how to model and quantify SCR behavior. This study proposes a new resilient supply chain metric that is incorporated into an optimization model to maximize economic and responsiveness objectives. A case study is conducted to analyze the impacts perceived by downstream customers and to demonstrate the correlation between SC performance and the new SCR metric.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Management
Tadeusz Sawik
Summary: A multi-portfolio approach and a scenario-based stochastic mixed integer program are developed to enhance the resilience of the supply chain, with a focus on the impact of unit penalty for unfulfilled demand on risk-averse supply portfolios. The findings show that the developed approach leads to a computationally efficient stochastic mixed integer program with a strong LP relaxation.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2021)
Review
Transportation
Rajali Maharjan, Hironori Kato
Summary: This study provides a comprehensive review of recent literature on resilient supply chain network design (RSCND), exploring and analyzing different resilience measures used in the literature and the benefits of incorporating them in supply chain network design. Although only a limited number of studies were found, this topic has great potential for future research.
Article
Green & Sustainable Science & Technology
R. Yazdanparast, F. Jolai, M. S. Pishvaee, A. Keramati
Summary: Drop-in biofuels have been widely used in developed countries as a means of reducing greenhouse gas emissions. However, the development of biofuels faces challenges such as the access to cheap fossil fuels, high construction costs of biorefineries, and potential disruptions in the biofuel supply chain. This paper proposes an optimization model that takes into account supply and production disruptions, and explores proactive strategies to improve the overall resilience of the supply chain. The model integrates planning and operational decisions to ensure economic and environmental sustainability.
Article
Green & Sustainable Science & Technology
Sina Nayeri, S. Ali Torabi, Mahdieh Tavakoli, Zeinab Sazvar
Summary: This study presents a multi-objective mixed-integer programming model for designing a sustainable supply chain network while taking into account resilience and responsiveness measures. By using a new optimization approach and meta-goal programming, the uncertainty in dynamic business environments is addressed. A case study in the water heater industry validates the effectiveness of the proposed model and solution approach, while offering useful insights through sensitivity analyses on key parameters.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Engineering, Industrial
Tadeusz Sawik, Bartosz Sawik
Summary: This paper applies stochastic optimisation of CVaR to maintain risk-averse viability and improve resilience of a supply chain under propagated disruptions. Two stochastic optimisation models are developed with conflicting objectives, and a stochastic mixed integer quadratic programming model is used to select a risk-averse viable production trajectory. The proposed approach is applied to smartphone manufacturing, and the findings show that more risk-aversive decision-making leads to a larger viability space and higher resilience of the supply chain. Single-objective decision-making may reduce supply chain viability.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Amirhossein Moadab, Ghazale Kordi, Mohammad Mahdi Paydar, Ali Divsalar, Mostafa Hajiaghaei-Keshteli
Summary: Effective supply chain management is crucial for economic growth and sustainability is a key consideration for large companies. This paper proposes a multi-objective mathematical linear model to optimize a sustainable, resilient, and responsive supply chain for PCR diagnostic tests. The model aims to minimize costs, negative societal impact, and environmental impact using a scenario-based approach. A real-life case study is conducted to validate the model, and sensitivity analyses are performed to analyze the behavior of the developed Mixed-Integer Linear Programming.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Green & Sustainable Science & Technology
Lida Safari, Seyed Jafar Sadjadi, Farzad Movahedi Sobhani
Summary: This paper addresses the issue of resilient sustainable supply chain design and planning under supply disruption risk. A multi-objective robust model is developed to solve the problem, considering various decisions related to supply chain design and planning. The proposed resilience strategies are found to be efficient in mitigating supply disruptions and maintaining supply chain sustainability.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2023)
Article
Engineering, Industrial
Keivan Tafakkori, Fariborz Jolai, Reza Tavakkoli-Moghaddam
Summary: This paper presents decentralized capacity planning models for different types of supply chain entities, aiming to enhance their resilience. Novel resilience metrics are developed to measure the proximity of capacities to disruptions, and optimization models are used to select business continuity plans that maximize resilience and cost-efficiency. Uncertainties associated with recovery time and disruptions are addressed using a robust-stochastic optimization method, and disruption scenarios are simulated using a discrete-time Markov chain. Computational tests confirm the robustness, validity, and generality of the proposed models.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Computer Science, Cybernetics
Mohammad Mahdi Vali-Siar, Emad Roghanian
Summary: This study proposes a novel mathematical model to address the resilient mixed supply chain network design problem, considering chain-to-chain competition under disruptions. The results indicate that considering resilience and applying related strategies are crucial for improving the supply chain objective and maintaining market share.
Article
Economics
M. Celeste Kees, J. Alberto Bandoni, M. Susana Moreno
Summary: This article presents a study on the management of blood supply chains in developing countries, addressing challenges such as collection methods, uncertainty in demand and supply, blood group distinction, and compatible substitutions. A multi-period mixed-integer linear programming model is formulated to minimize shortage, total costs, and number of substitutions. The model is then reformulated as a fuzzy mixed-integer goal programming one and solved using a compromise solution strategy. A real-life case study demonstrates the advantages of the approach in increasing demand satisfaction, reducing costs, substitutions, and wastes.
SOCIO-ECONOMIC PLANNING SCIENCES
(2022)
Article
Computer Science, Interdisciplinary Applications
Soumya Ranjan Pathy, Hamed Rahimian
Summary: Motivated by the disruptions in the global supply chain due to COVID-19, this study investigates the optimal procurement and inventory decisions in a pharmaceutical supply chain with uncertain and spatiotemporal demand. A two-stage optimization framework is proposed to address demand uncertainty, where the first stage minimizes the cost and risk associated with pre-positioning drugs, and the second stage minimizes the cost of recourse decisions. The study considers different risk preferences and proposes two models, stochastic programming and robust optimization, to capture the risk of demand uncertainty. Efficient algorithms are also proposed for solving these models.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Computer Science, Interdisciplinary Applications
Motahareh Rabbani, Seyyed Mohammad Hadji Molana, Seyed Mojtaba Sajadi, Mohammad Hossein Davoodi
Summary: This paper proposes a multi-objective, multi-product, multi-period mathematical model for sustainable phosphorus supply chain management in an uncertain environment. By considering environmental, social, and economic challenges, a sustainable-resilient supply chain network for the fertilizer industry is designed. Reactive strategy and robust stochastic programming are used to cope with uncertainties and disruptions, effectively controlling the uncertainty and risk-aversion of output decisions.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Engineering, Industrial
Xiaoyan Qian, Tava Lennon Olsen
Summary: This paper discusses the specific financial and risk management issues faced by agricultural cooperatives, using Fonterra as a case study. A Markov decision process model is proposed to aid decision-making and maximize shareholder returns while minimizing financial risks. Numerical experiments reveal the importance of trade-offs in financial decision-making and the effectiveness of designing risk management policies.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Polymer Science
Mohamed H. Abdel-Aziz, Mohammed Zwawi, Ahmed F. Al-Hossainy, Mohamed Sh. Zoromba
Summary: A semiconductor thin film of poly(o-phenylene diamine-co-m-phenylene diamine) copolymer [PoPmP] was fabricated via oxidative polymerization in an acidic solution, with a thickness of approximately 150 nanometers. Characterization of the copolymer was performed using various techniques, and its structure and optical properties were measured experimentally and computationally. The results suggest that the thin film shows promising potential as a candidate for polymer solar cell applications, highlighting its electronic transition properties.
POLYMERS FOR ADVANCED TECHNOLOGIES
(2021)
Article
Management
Haiyan Wang, Tava Lennon Olsen, Timofey Shalpegin
Summary: This study examines the impact of capacity and discount decisions in a service environment with seasonal arrival rates and strategic customers. The presence of strategic customers may benefit peak-time customers and lead to the supplier needing to offer lower discounts or build more capacity. Strategic customers exhibit follow-the-crowd behavior, and their presence is not advantageous for the service provider.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2022)
Article
Engineering, Industrial
Mohammed Adel Abdelmegid, Vicente A. Gonzalez, Michael O'Sullivan, Cameron G. Walker, Mani Poshdar, Luis Fernando Alarcon
Summary: This paper introduces a framework that integrates simulation modelling practices with the Last Planner System (LPS) to address the lagging simulation uptake in construction. The study shows that LPS provides a promising avenue for integration with simulation modelling, potentially minimizing data requirements and modelling efforts, thus improving simulation uptake in the construction industry.
PRODUCTION PLANNING & CONTROL
(2023)
Article
Computer Science, Theory & Methods
Seyedhamid Mashhadi Moghaddam, Michael O'Sullivan, Charles Peter Unsworth, Sareh Fotuhi Piraghaj, Cameron Walker
Summary: Cloud service providers use load balancing algorithms to avoid SLAVs and wasted energy consumption. A key consideration is the balance between reducing migrations and decreasing host over-utilization. The paper proposes an alternative metric that considers QoS for customer VMs and compares load balancing methods with both existing and new metrics.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2021)
Article
Health Care Sciences & Services
Kian Wee Soh, Thomas Lumley, Cameron Walker, Michael O'Sullivan
Summary: This paper presents a new model averaging technique for medical research, which partitions the dataset based on categorical variables and determines model averages by minimizing a form of squared errors. The study shows that this technique may outperform the well-established jackknife model averaging under certain assumptions and conditions. An example is also provided where a cross-validation procedure fails to determine the weights for model averaging.
STATISTICAL METHODS IN MEDICAL RESEARCH
(2022)
Review
Economics
Milad Asadpour, Tava Lennon Olsen, Omid Boyer
Summary: This article reviews the blood supply chain (BSC) in disaster situations, which has received increasing research attention in recent years. The authors provide a comprehensive review of quantitative models for BSCs, analyze solution methods, and offer practical directions for future research.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2022)
Article
Engineering, Manufacturing
Quan Zhou, Tava Lennon Olsen
Summary: Most developed countries hold significant quantities of medical supplies in reserve for emergencies. Unused reserve supplies that have expired without use pose a significant problem. Donating expired medical supplies to developing countries is a possible solution, despite caution from the international community. Research suggests that slightly lower quality expired donations may be more beneficial than fresh donations.
PRODUCTION AND OPERATIONS MANAGEMENT
(2023)
Article
Management
Xiaoyan Qian, Tava Lennon Olsen
Summary: This study proposes a two-stage stochastic program to investigate the quality coordination problem in agricultural cooperatives. The results show that the commonly used pooling payment scheme can only coordinate the supply chain when the farmers' time preference is higher than a threshold. Otherwise, it leads to over-motivation with respect to effort. However, the upfront incentive (UI) payment scheme can unconditionally coordinate the supply chain and is robust to farmers with different farm sizes.
M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT
(2022)
Article
Engineering, Industrial
Mojtaba Mahdavi, Mahdi Mahmoudzadeh, Tava Lennon Olsen
Summary: Fisher's (1997) conceptual framework of building efficient supply chains for functional products and responsive supply chains for innovative products is widely discussed in supply chain management. However, previous research lacks analytical guidelines. This paper develops a quantitative model to analyze decision-making and finds that overoptimism about forecast accuracy and overconfidence about service level are the main reasons for mismatching supply chains for innovative products.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2023)
Article
Operations Research & Management Science
Minh Do, Tiru Arthanari, Tava Lennon Olsen, Timofey Shalpegin, Shuaian Wang
Summary: This study investigates the impact of changes in the number of shipping lines on port charges and profits. A two-stage noncooperative game-theoretic model is developed, where ports determine their container handling charges in the first stage and shipping lines decide on the number of calls at each port in the second stage. Applying the model to the competition between the Port of Tauranga and the Port of Auckland in New Zealand provides managerial insights. The study extends existing literature on port competition by considering competition among shipping lines.
NAVAL RESEARCH LOGISTICS
(2023)
Article
Computer Science, Interdisciplinary Applications
T. Adams, M. O'Sullivan, C. Walker
Summary: This research aims to improve the prediction of surgical procedure duration by using medical ontological information. Two methods, one using medical terms and the other using text fragments, are presented and compared. The results show that both methods provide better prediction accuracy compared to traditional models.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2023)
Article
Computer Science, Interdisciplinary Applications
T. Adams, M. O'Sullivan, C. Walker, K. Wang, L. Boyle
Summary: Traditional objective functions for scheduling surgeries often lead to inequitable outcomes for patients in terms of waiting time. This study compares two objective functions (risk neutral and risk averse) using a mixed integer program and historical data. It also examines the effects of other model parameters on surgical schedules. The results show that the risk neutral objective can achieve similar schedules to the risk averse objective, with easier problem-solving.
COMPUTERS & OPERATIONS RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Mehrdad Amirghasemi, Michael O'Sullivan, Cameron Walker
Summary: Transportation, telecommunication, electricity supply, and production-distribution systems all require properly designed networks in order to function effectively. Network design problems are crucial for network-based decision making systems and have numerous industrial applications.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Brian S. Gu, Tharindu Dharmakeerthi, Seho Kim, Michael J. O'Sullivan, Grant A. Covic
Summary: This article proposes a reduced ferrite inductive power transfer system for electric vehicle charging, which uses ferrite-based soft magnetic composites to reduce system cost and improve mechanical robustness. The optimized system reduces ferrite volume by 63% and exhibits minimal deterioration in terms of coupling reduction and magnetic field leakage.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2023)
Review
Management
Vinicius N. Motta, Miguel F. Anjos, Michel Gendreau
Summary: This survey presents a review of optimization approaches for the integration of demand response in power systems planning and highlights important future research directions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Philipp Schulze, Armin Scholl, Rico Walter
Summary: This paper proposes an improved branch-and-bound algorithm, R-SALSA, for solving the simple assembly line balancing problem, which performs well in balancing workloads and providing initial solutions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Roshan Mahes, Michel Mandjes, Marko Boon, Peter Taylor
Summary: This paper discusses appointment scheduling and presents a phase-type-based approach to handle variations in service times. Numerical experiments with dynamic scheduling demonstrate the benefits of rescheduling.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Oleg S. Pianykh, Sebastian Perez, Chengzhao Richard Zhang
Summary: Efficient scheduling is crucial for optimizing resource allocation and system performance. This study focuses on critical utilization and efficient scheduling in discrete scheduling systems, and compares the results with classical queueing theory.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Review
Management
Hamed Jahani, Babak Abbasi, Jiuh-Biing Sheu, Walid Klibi
Summary: Supply chain network design is a large and growing area of research. This study comprehensively surveys and analyzes articles published from 2008 to 2021 to detect and report financial perspectives in SCND models. The study also identifies research gaps and offers future research directions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Patrick Healy, Nicolas Jozefowiez, Pierre Laroche, Franc Marchetti, Sebastien Martin, Zsuzsanna Roka
Summary: The Connected Max-k-Cut Problem is an extension of the well-known Max-Cut Problem, where the objective is to partition a graph into k connected subgraphs by maximizing the cost of inter-partition edges. The researchers propose a new integer linear program and a branch-and-cut algorithm for this problem, and also use graph isomorphism to structure the instances and facilitate their resolution. Extensive computational experiments show that, if k > 2, their approach outperforms existing algorithms in terms of quality.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Victor J. Espana, Juan Aparicio, Xavier Barber, Miriam Esteve
Summary: This paper introduces a new methodology based on the machine learning technique MARS for estimating production functions that satisfy classical production theory axioms. The new approach overcomes the overfitting problem of DEA through generalized cross-validation and demonstrates better performance in reducing mean squared error and bias compared to DEA and C2NLS methods.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Stefano Nasini, Rabia Nessah
Summary: In this paper, the authors investigate the impact of time flexibility in job scheduling, showing that it can significantly affect operators' ability to solve the problem efficiently. They propose a new methodology based on convex quadratic programming approaches that allows for optimal solutions in large-scale instances.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Zhiqiang Liao, Sheng Dai, Timo Kuosmanen
Summary: Nonparametric regression subject to convexity or concavity constraints is gaining popularity in various fields. The conventional convex regression method often suffers from overfitting and outliers. This paper proposes the convex support vector regression method to address these issues and demonstrates its advantages in prediction accuracy and robustness through numerical experiments.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Kuo-Hao Chang, Ying-Zheng Wu, Wen-Ray Su, Lee-Yaw Lin
Summary: The damage and destruction caused by earthquakes necessitates the evacuation of affected populations. Simulation models, such as the Stochastic Pedestrian Cell Transmission Model (SPCTM), can be utilized to enhance disaster and evacuation management. The analysis of SPCTM provides insights for government officials to formulate effective evacuation strategies.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Qinghua Wu, Mu He, Jin-Kao Hao, Yongliang Lu
Summary: This paper studies a variant of the orienteering problem known as the clustered orienteering problem. In this problem, customers are grouped into clusters and a profit is associated with each cluster, collected only when all customers in the cluster are served. The proposed evolutionary algorithm, incorporating a backbone-based crossover operator and a destroy-and-repair mutation operator, outperforms existing algorithms on benchmark instances and sets new records on some instances. It also demonstrates scalability on large instances and has shown superiority over three state-of-the-art COP algorithms. The algorithm is also successfully applied to a dynamic version of the COP considering stochastic travel time.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Bjorn Bokelmann, Stefan Lessmann
Summary: Estimating treatment effects is an important task for data analysts, and uplift models provide support for efficient allocation of treatments. However, evaluating uplift models is challenging due to variance issues. This paper theoretically analyzes the variance of uplift evaluation metrics, proposes variance reduction methods based on statistical adjustment, and demonstrates their benefits on simulated and real-world data.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Congzheng Liu, Wenqi Zhu
Summary: This paper proposes a feature-based non-parametric approach to minimizing the conditional value-at-risk in the newsvendor problem. The method is able to handle both linear and nonlinear profits without prior knowledge of the demand distribution. Results from numerical and real-life experiments demonstrate the robustness and effectiveness of the approach.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Laszlo Csato
Summary: This paper compares the performance of the eigenvalue method and the row geometric mean as two weighting procedures. Through numerical experiments, it is found that the priorities derived from the two eigenvectors in the eigenvalue method do not always agree, while the row geometric mean serves as a compromise between them.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Guowei Dou, Tsan-Ming Choi
Summary: This study investigates the impact of channel relationships between manufacturers on government policies and explores the effectiveness of positive incentives versus taxes in increasing social welfare. The findings suggest that competition may be more effective in improving sustainability and social welfare. Additionally, government incentives for green technology may not necessarily enhance sustainability.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
