Article
Management
Xingli Wu, Huchang Liao
Summary: Multiple criteria decision aiding aims to recommend decisions consistent with the decision-maker's preferences. This study introduces probabilistic linguistic preference relations and value functions to handle uncertain preference information and conducts consistency and robustness analysis. The empirical application verifies the effectiveness of the proposed model.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2023)
Article
Management
Krzysztof Martyn, Milosz Kadzinski
Summary: This study proposes preference learning algorithms for inferring the parameters of a sorting model from large sets of examples, with application in Multiple Criteria Decision Analysis. By utilizing artificial neural networks and gradient descent optimization algorithms, the study achieves high predictive accuracy.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Ridwan Pandiya, Gita Fadila Fitriana, Faisal Dharma Adhinata, Tenia Wahyuningrum
Summary: This paper introduces the methods of fuzzy analytic hierarchy process and logarithmic fuzzy preference programming, as well as the problems encountered in their application. It proposes an improved non-parameter transcendental fuzzy preference programming method, which is more reliable and efficient in obtaining optimal weights.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Management
Xingli Wu, Huchang Liao
Summary: Preference disaggregation is an effective approach for inducing preference models from empirical data, which is important for data-driven decision-making. However, existing techniques often overlook the interrelationship between criteria. To address this, the study proposes a compensatory value function that models the importance of criteria additively and describes interactions between criteria and decision makers' risk tolerance. The proposed preference disaggregation procedure using the compensatory value function shows promising results compared to other value functions that consider limited preference factors.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2023)
Article
Computer Science, Artificial Intelligence
Michal Wojcik, Milosz Kadzinski, Krzysztof Ciomek
Summary: This article discusses preference disaggregation in the context of multiple criteria sorting. The value function parameters and thresholds separating different classes are inferred from the Decision Maker's assignment examples. Different procedures for selecting a representative sorting model are reviewed, and three novel procedures implementing the robust assignment rule are presented. Experimental results show that the most efficient procedures in terms of classification accuracy, reproducing the DM's model, and delivering robust assignments include approaches identifying differently interpreted centers of the feasible polyhedron and the robust methods introduced in this paper. The impact of different numbers of classes, criteria, characteristic points, and reference assignments on the performance of all procedures is also discussed.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Management
Luis C. Dias, Joana Dias, Tiago Ventura, Humberto Rocha, Brigida Ferreira, Leila Khouri, Maria do Carmo Lopes
Summary: This article presents a new multi-criteria decision aiding preference disaggregation method based on an asymmetric target-based model. The method penalizes solutions that do not meet the target, representing the preferences of a radiation oncologist effectively in choosing radiotherapy treatment plans.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Review
Management
Milosz Kadzinski, Michal Wojcik, Krzysztof Ciomek
Summary: This article discusses the preference disaggregation setting in the context of multiple criteria ranking and choice problems. It reviews methods for constructing consistent recommendations and compares their performance in terms of reconstructing decision makers' preferences and delivering robust recommendations. The study also examines the impact of different parameterizations on the performance of these methods.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2022)
Article
Computer Science, Information Systems
Juan Carlos Leyva Lopez, Efrain Solares, Jose Rui Figueira
Summary: This paper focuses on hierarchical multiple criteria ranking problems and proposes an aggregation-disaggregation approach using an evolutionary algorithm to infer the model parameters. The proposed method allows indirect elicitation of the parameters through a ranking of reference alternatives and additional preference information.
INFORMATION SCIENCES
(2022)
Article
Computer Science, Artificial Intelligence
Milosz Kadzinski, Krzysztof Martyn, Marco Cinelli, Roman Slowinski, Salvatore Corrente, Salvatore Greco
Summary: The paper addresses a problem of multi-decision sorting subject to multiple criteria and presents a new method for dealing with such a problem, including a threshold-based value-driven sorting procedure and constructing interrelated preference models. The practical usefulness of the approach is demonstrated through a case study on risk management related to nanomaterials, highlighting the inferred preference models that can support health and safety managers in reducing associated risks.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Shuxian Sun, Huchang Liao
Summary: This study proposes a value-driven multiple criteria sorting procedure that considers uncertain assignment examples with probabilistic linguistic information. By introducing probability linguistic term set and weighted additive value function, decision-makers' preferences can be more comprehensively reflected.
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
(2022)
Article
Management
Daniel De Wolf, Yves Smeers
Summary: The article presents a characterization of the Clarke subdifferential of the optimal value function of a linear program in terms of matrix coefficients. It generalizes the result of Freund (1985) to situations where derivatives may not be defined due to the presence of multiple primal or dual solutions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Ecology
Pirta Palola, Richard Bailey, Lisa Wedding
Summary: Traditional environmental valuation methods have focused on total and absolute values, neglecting value pluralism and marginal changes. This study introduces a new valuation framework, Environmental Value Functions (EVF), which incorporates value pluralism and marginal value analysis.
ECOLOGICAL ECONOMICS
(2022)
Article
Environmental Sciences
Alice H. Aubert, Sara Schmid, Philipp Beutler, Judit Lienert
Summary: Investigating wastewater management matters: in many OECD countries, the conventional centralized system is reaching its limits. Alternative decentralized options exist. Citizen participation is challenging because they are numerous and need to learn about the topic and construct their opinion. To include citizens, an innovative online survey based on Multi-Attribute Value Theory (MAVT) is proposed. The survey helped citizens understand the complex decision and construct their preferences. The study provides insights for wastewater management and evaluates the effectiveness of the survey method.
ENVIRONMENTAL SCIENCE & POLICY
(2022)
Article
Management
Mehdi Bagherzadeh, Mohammad Ghaderi, Anne-Sophie Fernandez
Summary: This study explores the impact of sourcing from competitors on innovation using a data-driven model. The findings suggest that sourcing from competitors can enhance innovation performance for financially constrained firms, but has a negative impact on firms receiving financial support, especially small ones. Firm characteristics, such as size and financial capability, play a key role in determining the relationship between coopetition and innovation performance.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Management
Sally Giuseppe Arcidiacono, Salvatore Corrente, Salvatore Greco
Summary: This paper introduces a method to handle multiple compatible value functions in multi-criteria decision making by building a probability distribution. Stochastic multicriteria acceptability analysis provides statistical information based on the decision maker's preferences. Extensive simulations and sensitivity analysis have been conducted to demonstrate the superiority of the proposed method.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2024)
Article
Computer Science, Artificial Intelligence
Francisco Javier Ruiz, Nuria Agell, Cecilio Angulo, Monica Sanchez
COGNITIVE SYSTEMS RESEARCH
(2018)
Article
Computer Science, Artificial Intelligence
Jordi Montserrat-Adell, Zeshui Xu, Xunjie Gou, Nuria Agell
INFORMATION FUSION
(2019)
Article
Computer Science, Artificial Intelligence
Jordi Montserrat-Adell, Nuria Agell, Monica Sanchez, Francisco Javier Ruiz
INFORMATION FUSION
(2018)
Article
Management
Milosz Kadzinski, Mohammad Ghaderi, Maciej Dabrowski
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2020)
Article
Computer Science, Artificial Intelligence
Jennifer Nguyen, Jordi Montserrat-Adell, Nuria Agell, Monica Sanchez, Francisco J. Ruiz
NEURAL COMPUTING & APPLICATIONS
(2020)
Article
Management
Mohammad Ghaderi, Milosz Kadzinski
Summary: This paper introduces an analytical framework for estimating individuals' preferences by uncovering structural patterns that regulate general shapes of value functions and found that considering structural patterns at the population level considerably improves the predictive performance of the constructed value functions at the individual level.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2021)
Article
Management
Mohammad Ghaderi
Summary: This paper proposes a unified agent-based modeling framework for policy decisions related to pandemics. The framework considers sources of uncertainty in the system and combines macro and micro-level attributes to generate comprehensive results.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Management
Mehdi Bagherzadeh, Mohammad Ghaderi, Anne-Sophie Fernandez
Summary: This study explores the impact of sourcing from competitors on innovation using a data-driven model. The findings suggest that sourcing from competitors can enhance innovation performance for financially constrained firms, but has a negative impact on firms receiving financial support, especially small ones. Firm characteristics, such as size and financial capability, play a key role in determining the relationship between coopetition and innovation performance.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Jennifer Nguyen, Albert Armisen, Nuria Agell, Angel Saz-Carranza
Summary: Global policy makers need to monitor global governance and utilize analytical tools such as global news dashboards to provide current information on global sentiment changes, particularly by identifying unexpected shifts in sentiment following major events. This paper introduces a methodology to evaluate global sentiment before, during, and after significant events, utilizing hesitant linguistic terms to represent sentiment in news articles and aggregating them into centralized sentiments for each period. The approach is able to detect changes in aggregated sentiment and consensus, providing a more sensitive model compared to traditional crisp aggregation methods for informing policy makers about public opinion and discourse.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2022)
Article
Engineering, Industrial
Bingjie Ding, Xavier Ferras Hernandez, Nuria Agell Jane
Summary: This study is the first systematic literature review that links Industry 4.0 with lean and agile manufacturing. The study proposes a conceptual framework that shows how Industry 4.0 supports both manufacturing systems and how they facilitate the implementation of Industry 4.0. The integration of Industry 4.0 with lean manufacturing enhances cost competitiveness, while with agile manufacturing, it enhances flexibility.
PRODUCTION PLANNING & CONTROL
(2023)
Article
International Relations
Angel Saz-Carranza, Marie Vandendriessche, Jenn Nguyen, Nuria Agell
Summary: The study found that the EU's role as an observer or member in an IGO significantly and positively influences the quantity of interactions, while also increasing the conflict level. Policy overlap between the EU and the IGO also increases the conflict level in their interactions.
JOURNAL OF EUROPEAN INTEGRATION
(2022)
Article
International Relations
Oscar Fernandez, Marie Vandendriessche, Angel Saz-Carranza, Nuria Agell, Javier Franco
Summary: The 2022 Russian invasion of Ukraine had a significant impact on Europe, leading to policy changes and shifts in public opinion on security and defense matters. This article analyzes how EU public opinion has been influenced by the war, finding that the invasion has intensified existing trends rather than fundamentally changing them.
JOURNAL OF EUROPEAN INTEGRATION
(2023)
Article
Computer Science, Artificial Intelligence
Walaa Abuasaker, Jennifer Nguyen, Francisco J. Ruiz, Monica Sanchez, Nuria Agell
Summary: In decision making under uncertainty, people often express their opinions in linguistic terms, but the meanings of these terms may not align. This paper studies the mathematical properties of the projection function and introduces an interpretation function, aiming to aggregate opinions onto a common perceptual map and translate the results back to individual maps. The empirical study shows that utilizing distinct perceptual maps for each user profile improves consensus statistically.
APPLIED SOFT COMPUTING
(2023)
Article
Education & Educational Research
David Riu, Monica Casabayo, Josep M. Sayeras, Xari Rovira, Nuria Agell
Summary: This paper introduces a methodology to assess university curricula by measuring the gap between graduate perceptions of their training and its workplace utility, providing rankings and guidelines for enhancements.
EDUCATIONAL REVIEW
(2022)
Article
Economics
Marius Matei, Xari Rovira, Nuria Agell
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)
