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)
Review
Green & Sustainable Science & Technology
Pablo Becerra, Josefa Mula, Raquel Sanchis
Summary: This paper provides a systematic review and classification of 91 studies on quantitative methods of green supply chains for sustainable inventory management. It identifies main study areas, findings, and quantitative models, setting a point for future research opportunities. The focus is on different supply chain designs and comparative analysis of mathematical programming, simulation, and statistical models.
JOURNAL OF CLEANER PRODUCTION
(2021)
Review
Management
Shupeng Huang, Andrew Potter, Daniel Eyers, Qinyun Li
Summary: This paper examines the influence of online review adoption on supply chain profitability under the presence of capacity constraint through mathematical modeling and simulation. The findings suggest that online reviews can bring more profit to the supply chain, although this influence is influenced by other variables such as capacity constraint level, lost sales penalty level, and product quality estimation.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2021)
Article
Green & Sustainable Science & Technology
Svetlana Nikolicic, Milorad Kilibarda, Marinko Maslaric, Dejan Mircetic, Sanja Bojic
Summary: This paper focuses on waste reduction in the dairy distribution chain by improving the inventory management system using modern information and communication technologies (ICT). Through testing and verifying a case study with simulation modeling, it is confirmed that coordinated inventory management supported by modern ICT can significantly improve the sustainability of the food supply chain.
Article
Green & Sustainable Science & Technology
Pablo Becerra, Josefa Mula, Raquel Sanchis
Summary: This article provides an overview of sustainable inventory management models in supply chains and proposes a roadmap for future research. The study reveals a lack of research on incorporating social sustainability into inventory management in supply chains, while environmental sustainability is a growing research area. Future studies should focus on incorporating uncertainty issues into sustainable inventory management models and integrating economic, environmental, and social sustainability decisions. Additionally, complex models and new algorithms and heuristics should be employed to address these issues effectively.
Article
Engineering, Industrial
Olatunde A. Durowoju, Hing Kai Chan, Xiaojun Wang, Temidayo Akenroye
Summary: Supply chain reconfiguration decisions have traditionally been driven by operational risk, while simplification and networking strategies have been shown to improve financial performance. However, the impact of information security breaches on these strategies remains unclear. This study found that the effects of security breaches on simplification and risk pooling strategies varied under different order replenishment systems.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2021)
Article
Computer Science, Interdisciplinary Applications
Young-Bin Woo, Ilkyeong Moon, Byung Soo Kim
Summary: This paper introduces a new production-inventory control model for a vertically integrated supply chain network, aiming to minimize total network cost and prevent inventory shortages and shutdown periods. Closed-form functions and a mixed-integer linear programming formulation are proposed, along with an algorithm to reduce computational burden. A case study demonstrates the application of the proposed model.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Chi-Jie Lu, Ming Gu, Tian-Shyug Lee, Chih-Te Yang
Summary: An integrated multistage supply chain inventory model is proposed to consider deteriorating raw materials and finished products. The model takes into account imperfect production and inspection systems. The main objective is to determine the optimal strategies for the manufacturer and retailers to maximize the integrated total profit. The research findings provide insights on the impact of various factors on the supply chain performance.
Article
Energy & Fuels
Jia-Liang Pan, Chui-Yu Chiu, Kun-Shan Wu, Chih-Te Yang, Yen-Wen Wang
Summary: This paper investigates a sustainable production-inventory model with considerations for carbon emission reduction technology and demand dependent on price and advertisement. The study aims to determine optimal pricing, advertising, production, inventory, and capital investment decisions under different carbon emission policies to maximize total profit in a multi-stage supply chain system. The model is verified through numerical examples and provides management implications for decision makers.
Article
Engineering, Industrial
Biswajit Sarkar, Mitali Sarkar, Baishakhi Ganguly, Leopoldo Eduardo Cardenas-Barron
Summary: The cleaning of waste in a production system under sustainable supply chain management is crucial for industries, with a focus on improving product quality and controlling carbon emissions. This study presents a three-echelon sustainable supply chain model, aiming to reduce costs and enhance sustainability through reducing defective products and carbon emissions. Numerical experiments and sensitivity analysis validate the model's effectiveness in achieving global optimum solutions and reducing carbon emissions.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2021)
Article
Engineering, Multidisciplinary
H. Abdullah Ali Ahmadini, Umar Muhammad Modibbo, Ali Akbar Shaikh, Irfan Ali
Summary: In this study, a multi-objective inventory model with green investment is proposed to address the increasing pressure to conserve the environment from global warming. The model is formulated as a multi-objective fractional programming problem with various objectives and constraints, aiming to provide useful suggestions to decision-makers in the manufacturing sectors.
ALEXANDRIA ENGINEERING JOURNAL
(2021)
Article
Operations Research & Management Science
Hamed Shourabizadeh, O. Erhun Kundakcioglu, Cem Deniz Caglar Bozkir, Mihriban Busra Tufekci, Andrea C. Henry
Summary: We studied inventory review policy for healthcare facilities to minimize the impact of inevitable drug shortages. Our proposed Markov chain model demonstrated significant economic impact of inventory parameter optimization.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Fatemeh Ghasemzadeh, Dragan Pamucar
Summary: Motivated by a dairy supply chain case, this study examines the management of deteriorating inventories in a three-echelon supply chain network with a local retailer having multiple customers. The customers are divided into two clusters in the downstream with different, uncertain demand functions: many small ordinary customers and few large premier customers. The goal is to determine the optimal inventory policy considering the time-sensitive deterioration rate of the product. The model is formulated using queuing theory and finite-horizon Semi-Markov process, and an integrated inventory system at the network level. Two solution approaches, adaptive Invasive Weed Optimization and Adaptive Heuristic Method, are designed to solve the nonlinear and nonconvex problem, with the former providing better solution quality and the latter being faster in computation. Sensitivity analyses show that perishability has a greater impact than uncertainty when facing both factors.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Review
Energy & Fuels
Md Abu Helal, Nathaniel Anderson, Yu Wei, Matthew Thompson
Summary: Based on current trends and policies, the potential growth of biomass-to-bioenergy conversion depends on the development of efficient, sustainable, and competitive biomass supply chains. A literature review using advanced bibliometric analysis and visualization identified research gaps and opportunities, such as globalization of supply chain research and the application of machine learning in this field. The results can guide stakeholders in addressing challenges and aid researchers in developing impactful studies.
Article
Engineering, Multidisciplinary
C-C Chang, C-J Lu, C-T Yang
Summary: This paper investigates a multistage production-inventory model for deteriorating items and examines the optimal strategies for the retailer and manufacturer based on collaborative preservation technology investment, aiming to maximize the total profit of the integrated system. Mathematical programming analysis is employed to determine the optimal solutions, and numerical examples are presented to illustrate the solution process and verify the concavity of the proposed model. Sensitivity analyses are conducted to examine the impact of major parameters on the optimal number of shipments.
Article
Management
Victor Gimenez, Francisco Javier Ayvar-Campos, Jose Cesar Lenin Navarro-Chavez
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2017)
Article
Economics
Victor Gimenez, William Prieto, Diego Prior, Emili Tortosa-Ausina
SOCIO-ECONOMIC PLANNING SCIENCES
(2019)
Article
Environmental Sciences
Mercedes Beltran-Esteve, Victor Gimenez, Andres J. Picazo-Tadeo
SCIENCE OF THE TOTAL ENVIRONMENT
(2019)
Article
Engineering, Civil
Jose Luis Zafra-Gomez, Victor Gimenez-Garcia, Cristina Maria Campos-Alba, Emilio Jose de la Higuera-molina
WATER RESOURCES MANAGEMENT
(2020)
Article
Economics
Victor Gimenez, Claudio Thieme, Diego Prior, Emili Tortosa-Ausina
Summary: Early intervention in quality education is a way to promote equal opportunities, and preschool education has become an important focus of public policy. This study evaluates the performance of preschool education centers in Chile that cater to children from lower socioeconomic families and proposes a valid methodology for decision making. It also quantifies the levels of effectiveness and emphasizes the importance of targeting efforts on centers that are more likely to have lower levels of effectiveness due to structural conditions.
SOCIO-ECONOMIC PLANNING SCIENCES
(2022)
Article
Economics
Alexei Arbona, Victor Gimenez, Sebastian Lopez-Estrada, Diego Prior
Summary: This study uses the metafrontier Malmquist-Luenberger index to measure changes in the productivity of schools in the Colombian education system. The results indicate deterioration in both public and private schools, with significant gaps between different subjects.
SOCIO-ECONOMIC PLANNING SCIENCES
(2022)
Article
Business
Rima Sermontyte-Baniule, Asta Pundziene, Victor Gimenez, Isabel Narbon-Perpina
Summary: This study investigates the impact of cultural dimensions and dynamic capabilities on the value-based performance of digital healthcare services, finding a correlation between cultural dimensions and dynamic capabilities, particularly in terms of environment scanning, employee engagement, and organizational learning, with strong dynamic capabilities associated with more advanced implementation of digital healthcare services.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2022)
Article
Economics
Erik Alda, Victor Gimenez, Irvin Gilberto Paz Castro, America Ivonne Zamora Torres
Summary: This study utilized a standard metafrontier model to evaluate the efficiency of customs offices in Mexico. The findings revealed that border customs offices had the highest within-group variations, whereas internal customs offices maintained constant efficiency and maritime customs offices were closest to the metafrontier. Additionally, border customs offices were the most productive group during the study period, although they were distant from the metafrontier. This research contributes to the existing literature on customs efficiency measurement.
Article
Engineering, Industrial
Asta Pundziene, Neringa Gerulaitiene, Sea Matilda Bez, Irene Georgescu, Christopher Mathieu, Jordi Carrabina-Bordoll, Josep Rialp-Criado, Hannu Nieminen, Alpo Varri, Susanne Boethius, Mark van Gils, Victor Gimenez-Garcia, Isabel Narbon-Perpina, Diego Prior-Jimenez, Laura Vilutiene
Summary: This study examines the impact of a social-purpose-driven ecosystem on value capture from digital health platforms. The social-purpose-driven ecosystem is characterized by seeking social impact before profits and empowering citizens for individual and collective well-being. The study finds that capturing value from digital healthcare platforms embedded in a social-purpose-driven ecosystem requires considering unique contingencies such as multilayer value creation, multipurpose complementary assets, emerging dominant design, and distributed socio-economic returns mechanisms. The study emphasizes the importance of acknowledging the contextual effect of a social-purpose-driven ecosystem and highlights the factors that can positively affect value capture from digital healthcare platforms.
Article
Economics
Francisco Javier Ayvar-Campos, Jose Cesar Lenin Navarro-Chavez, Victor Gimenez
JOURNAL OF ECONOMICS FINANCE AND ADMINISTRATIVE SCIENCE
(2020)
Article
Business
Victor Gimenez, Diego Prior, Jorge R. Keith
ACADEMIA-REVISTA LATINOAMERICANA DE ADMINISTRACION
(2020)
Article
Economics
Erik Alda, Victor Gimenez, Diego Prior
APPLIED ECONOMICS LETTERS
(2020)
Article
Health Policy & Services
Victor Gimenez, Jorge R. Keith, Diego Prior
HEALTH CARE MANAGEMENT SCIENCE
(2019)
Article
Social Sciences, Interdisciplinary
Victor Gimenez, Claudio Thieme, Diego Prior, Emili Tortosa-Ausina
SOCIAL INDICATORS RESEARCH
(2019)
Article
Business
Victor Gimenez, Claudio Thieme, Diego Prior, Emili Tortosa-Ausina
JOURNAL OF PRODUCTIVITY ANALYSIS
(2017)
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)
