Article
Computer Science, Interdisciplinary Applications
J. C. Chacon-Hurtado, L. Scholten
Summary: Environmental decisions are complex due to their multidimensional nature, involving multiple stakeholders and uncertain consequences. Decisi-o-rama, an open-source Python MCDA library, addresses the challenges by focusing on usability, uncertainty awareness, computational efficiency, and integration with portfolio decisions, facilitating the adoption of MCDA methods in environmental decision-making.
ENVIRONMENTAL MODELLING & SOFTWARE
(2021)
Article
Economics
Eduardo Fernandez, Jose Rui Figueira, Jorge Navarro, Efrain Solares
Summary: This paper proposes a generalized method for multi-criteria decision-making analysis in an interval framework, which can handle uncertainty and fuzziness. By modeling interval numbers, the method allows estimation of decision model parameters and assessment of criteria performance levels.
SOCIO-ECONOMIC PLANNING SCIENCES
(2022)
Article
Automation & Control Systems
Sisi Xia, Haoran Yang, Lin Chen
Summary: This paper proposes a new decision-making approach based on soft set theory to solve MCDM problems with redundant and incomplete information. The proposed algorithm directly operates on the original data set without the need to transform incomplete information into complete one, avoiding potential bad decision-making due to information loss or unreliable assumptions about data generating mechanism. The practical application of the method in a regional food safety evaluation problem in Chongqing, China, demonstrates its effectiveness.
INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE
(2021)
Article
Computer Science, Information Systems
Jiang Deng, Jianming Zhan, Wei-Zhi Wu
Summary: This article proposes a ranking method based on preference relations for addressing multi-criteria decision-making problems in incomplete multi-scale information systems. The method is validated through a numerical example and comparative study, demonstrating its usefulness and effectiveness.
INFORMATION SCIENCES
(2022)
Article
Management
Byeong Seok Ahn
Summary: This paper proposes a method for ranking discrete alternatives with incomplete attribute weights. The approach solves a linear programming problem to determine dominance relations between alternatives. By exploring the dual problem, closed-form solutions and extreme points of ranked attribute weights are identified. The method is extended to handle incomplete attribute weights and linear inequalities. A case study demonstrates how the dual approach establishes dominance between alternatives with specified preference orders.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2023)
Article
Engineering, Mechanical
Dimitrios G. Giovanis, Michael D. Shields
Summary: The objective of this study is to quantify the uncertainty in probability of failure estimates resulting from incomplete knowledge of the probability distributions for the input random variables. The study proposes a framework that combines Subset Simulation (SuS) with Bayesian/information theoretic multi-model inference, and through methods such as multi-model inference and importance sampling, empirical probability distributions of failure probabilities that provide direct estimates of the uncertainty in failure probability estimates are obtained.
PROBABILISTIC ENGINEERING MECHANICS
(2022)
Article
Economics
Charles F. Manski, Aleksey Tetenov
Summary: In this study, researchers explored treatment choice for COVID-19 from the perspective of statistical decision theory. By utilizing the concept of near-optimality, they found that the empirical success rule yields treatment choices much closer to optimal compared to prevailing decision criteria based on hypothesis tests.
Article
Computer Science, Artificial Intelligence
Xianfeng Huang, Jianming Zhan, Zeshui Xu, Hamido Fujita
Summary: This paper proposes a prospect-regret theory-based three-way decision model for solving incomplete multi-scale decision information system problems. By selecting the optimal scale combination, evaluating attribute weights, and constructing aggregated weighted fuzzy conditional probabilities, the model achieves excellent performance in experiments.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Management
Kolos Csaba Agoston, Laszlo Csato
Summary: This paper generalizes Saaty's famous rule of thumb for the acceptable level of inconsistency to incomplete pairwise comparison matrices by minimizing the maximal eigenvalue of the incomplete matrix through choosing missing elements.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2022)
Article
Computer Science, Artificial Intelligence
Nana Liu, Zeshui Xu, Hangyao Wu
Summary: This paper proposes a multi-attribute group decision-making (MAGDM) method for incomplete linear ordinal ranking (ILOR) information combined with the decision field theory (DFT) from the perspective of process-oriented decision-making. The method improves the extended preference map and information energy for ILOR and introduces the concept of probabilistic utility set (PUS) to enhance the computability of ILOR. The framework and detailed steps of the DFT-combined MAGDM method are presented, and the method is illustrated to show its usage and features.
APPLIED SOFT COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Nahla Ben Amor, Helene Fargier, Regis Sabbadin, Meriem Trabelsi
Summary: This paper proposes a representation framework for ordinal games under possibilistic incomplete information and extends the fundamental notions of pure and mixed Nash equilibrium to this framework. The article shows that deciding whether a pure Nash equilibrium exists is a difficult task (NP-hard) and proposes a Mixed Integer Linear Programming (MILP) encoding of the problem. Additionally, the paper demonstrates that computing a possibilistic mixed equilibrium can be solved in polynomial time.
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
(2022)
Article
Management
Jozsef Temesi, Zsombor Szadoczki, Sandor Bozoki
Summary: The method of pairwise comparisons is used to rank top women tennis players based on their win/lose ratios. Incomplete pairwise comparison matrices were constructed from data obtained from the WTA homepage. The weight vector was calculated using the logarithmic least squares method and the eigenvector method. The results show the ranking of players and indicate the significance of nontransitive triads.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2023)
Article
Computer Science, Information Systems
Grzegorz Miebs, Milosz Kadzinski
Summary: The researchers propose a heuristic method for constructing compromise incomplete rankings based on partial rankings allowing for incomparability. The algorithms utilize various optimization techniques and are demonstrated to be effective through a real-world case study and experimental comparisons on artificially generated problems.
INFORMATION SCIENCES
(2021)
Article
Geography
Amanda Gadelha Ferreira Rosa, Caroline Maria de Miranda Mota, Ciro Jose Jardim de Figueiredo
Summary: This paper utilizes a multi-methodology framework to study violence in public spaces. By employing a geographic information system (GIS) and a multi-criteria decision analysis (MCDA) model, the study explores the incidence of street robberies and classifies the study area into different levels of vulnerability. The findings reveal spatial and statistical associations between social interaction features, bus stops, and street robberies, as well as identify socio-demographic dimensions such as makeshift houses, literacy rates, and population as factors contributing to crime. The holistic analysis provided by the multi-methodology framework enhances understanding of urban spaces and aids in identifying vulnerability to crime.
Article
Computer Science, Artificial Intelligence
Jose Luis Garcia-Lapresta, Pablo Moreno-Albadalejo, David Perez-Roman, Victor Temprano-Garcia
Summary: A new multi-criteria procedure is devised for new product development decision-making based on survey data. This procedure evaluates different product categories using qualitative scales and ordinal proximity measures, ranking the products without cardinalization procedures.
APPLIED SOFT COMPUTING
(2021)
Article
Operations Research & Management Science
Luis C. Dias, Carolina Passeira, Joao Malca, Fausto Freire
Summary: This article compares the environmental impacts of four different Rapeseed Methyl Ester biodiesel production chains from different feedstock origins. The study applies a combination of Life Cycle Assessment (LCA) and Multi-Criteria Decision Analysis (MCDA) to evaluate the various impact categories. Two different MCDA methods are used to address the weighting issue in the LCA research and studies. The proposed LCIA-MCDA approach aims to assess robust conclusions without specific weightings.
ANNALS OF OPERATIONS RESEARCH
(2022)
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)
Article
Management
Anna Labijak-Kowalska, Milosz Kadzinski, Inga Spychala, Luis C. Dias, Javier Fiallos, Jonathan Patrick, Wojtek Michalowski, Ken Farion
Summary: This study proposes a novel variant of the value-based additive data envelopment analysis model and conducts a comprehensive robustness analysis of physicians' performance using mathematical programming and the Monte Carlo simulation. The results indicate a strong dependence of physicians' performances on the selected weight vectors, and provide a basis for identifying overall good performers, developing improvement plans, and recognizing challenging patients' complaints.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2023)
Review
Environmental Sciences
Murilo R. Santos, Luis C. Dias, Maria C. Cunha, Joao R. Marques
Summary: This paper provides a systematic review of studies that utilized multicriteria decision analysis (MCDA) to address plastic waste management. The review included 20 relevant papers published from 2008 to 2021, covering case studies in three continents. The findings suggest that alternative solutions were identified for almost all types of plastic disposal methods. The most commonly used method was AHP, followed by TOPSIS and outranking methods.
FRONTIERS IN MARINE SCIENCE
(2022)
Article
Management
Jorge Noro, Luis C. Dias
Summary: This article presents a new bi-objective optimization model for project portfolio management, aiming to improve team performance by maximizing the economic gains of the project portfolio and the skills development of the allocated agents. The model selects project implementers and considers the workload and distribution of work's impact on employment commitment.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2023)
Article
Environmental Sciences
Maria C. Cunha, Joao Marques, Luis C. Dias, Ignacio Rada Cotera, George Triantaphyllidis
Summary: This paper explores the important factors for assessing new marine litter reduction and processing technologies through the Delphi method. The study highlights the relevant technology features and gathers valuable data in areas lacking information. By involving recognized experts and stakeholders, the study determines the consensus and perception of the importance for each aspect. The findings provide a list of factors to consider in different decision-making contexts, taking into account technical, environmental, socio-economic, and political issues.
FRONTIERS IN MARINE SCIENCE
(2022)
Article
Management
Luis C. Dias, Rudolf Vetschera
Summary: This article presents a model for a two-party bargaining process that involves multiple offers with a risk of breakdown. By considering confidence as a factor, the study offers a new perspective on the bargaining process. Analytical results show that under certain assumptions, the bargaining process converges to the nonsymmetric Nash bargaining solution.
GROUP DECISION AND NEGOTIATION
(2022)
Article
Environmental Sciences
Luis C. Dias, Maria C. Cunha, Emma Watkins, George Triantaphyllidis
Summary: This study evaluated policy options for the EU marine litter strategy using a multi-criteria decision analysis method. The results showed that revising the Urban Wastewater Treatment Directive, setting legislative targets on marine litter, and funding proven clean-up technologies are the most potentially impactful policies, while others can also play an important complementary role.
MARINE POLLUTION BULLETIN
(2022)
Article
Operations Research & Management Science
Luis C. Dias, Humberto Rocha
Summary: This study proposes a stochastic method based on Markov solution for selecting the most preferred alternative. It can be used to exploit different types of outranking relations and guarantees important properties with minimal computation effort.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Environmental Sciences
A. Luis Amaral, Rita Martins, Luis C. Dias
Summary: This study characterizes and benchmarks the wastewater treatment sector in Portugal and identifies the best practices in resource efficiency. The analysis reveals the positive impact of service providers' size and certifications on efficiency, while underuse of treatment plants negatively affects efficiency. These findings provide valuable insights for strategic policies in the water sector and can be applied to identify role models in other countries.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2022)
Article
Management
Luis C. Dias, Benjamin Lev, James B. Anderson
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2023)
Article
Green & Sustainable Science & Technology
Antonio L. Amaral, Rita Martins, Luis C. Dias
Summary: Identifying the main drivers of performance is essential for enhancing the sustainability of water utilities. This study aims to identify the relevant drivers associated with sustainability-related operational indicators in both drinking water supply and wastewater treatment. Various data analysis methods, including cross correlations analysis, clustering analysis, and principal components analysis, were employed to investigate the interrelationships between variables and capture important information. The results emphasize the importance of service provider size, personnel allocation, water losses, and certification policies in influencing operational indicators. Policy recommendations include promoting the aggregation of smaller service providers, controlling water losses and personnel allocation, and implementing certification practices.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Management
Rudolf Vetschera, Luis C. Dias
Summary: In this study, the researchers examined the compatibility between a dynamic bargaining model and observations from negotiation experiments. They found that the model was largely compatible with the observed bargaining processes, but actual agreements tended to be more balanced than predicted by the model. Additionally, they discovered a strong relationship between negotiator confidence and their independently ascertained aspiration levels, providing further evidence for the model's external validity.
EURO JOURNAL ON DECISION PROCESSES
(2023)
Article
Green & Sustainable Science & Technology
Jade Muller-Carneiro, Carla Rodrigues, Luis C. Dias, Carlos Henggeler Antunes, Adriano L. A. Mattos, Fausto Freire
Summary: This article proposes a framework combining ex-ante life cycle assessment (LCA) with multi-criteria decision analysis (MCDA) for the evaluation of novel bio-based materials. The framework is applied to starch films for food packaging and compares them with commercial polymers based on cost, environmental, and technical criteria. The results show that the commercial polymers outperform the novel films in terms of technical performance, but the starch films have potential for rigid applications.
JOURNAL OF CLEANER PRODUCTION
(2023)
Proceedings Paper
Green & Sustainable Science & Technology
Antonio L. Amaral, Rita Martins, Luis C. Dias
Summary: To improve the sustainability of the water sector, it is crucial to identify top-performing service providers and understand the factors driving their performance.
TECHNOLOGIES, MARKETS AND POLICIES: BRINGING TOGETHER ECONOMICS AND ENGINEERING
(2022)
Article
Computer Science, Interdisciplinary Applications
Rafael Praxedes, Teobaldo Bulhoes, Anand Subramanian, Eduardo Uchoa
Summary: The Vehicle Routing Problem with Simultaneous Pickup and Delivery is a classical optimization problem that aims to determine the least-cost routes while meeting pickup and delivery demands and vehicle capacity constraints. In this study, a unified algorithm is proposed to solve multiple variants of the problem, and extensive computational experiments are conducted to evaluate the algorithm's performance.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Ragheb Rahmaniani, Teodor Gabriel Crainic, Michel Gendreau, Walter Rei
Summary: Benders decomposition (BD) is a popular solution algorithm for stochastic integer programs. However, existing parallelization methods often suffer from inefficiencies. This paper proposes an asynchronous parallel BD method and demonstrates its effectiveness through numerical studies and performance enhancement strategies.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Giulia Caselli, Maxence Delorme, Manuel Iori, Carlo Alberto Magni
Summary: This study addresses a real-world scheduling problem and proposes four exact methods to solve it. The methods are evaluated through computational experiments on different types of instances and show competitive advantages on specific subsets. The study also demonstrates the generalizability of the algorithms to related scheduling problems with contiguity constraints.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Shaowen Yao, Chao Tang, Hao Zhang, Songhuan Wu, Lijun Wei, Qiang Liu
Summary: This paper examines the problem of two-dimensional irregular multiple-size bin packing and proposes a solution that utilizes an iteratively doubling binary search algorithm to find the optimal bin combination, and further optimizes the result through an overlap minimization approach.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Decheng Wang, Ruiyou Zhang, Bin Qiu, Wenpeng Chen, Xiaolan Xie
Summary: Consideration of driver-related constraints, such as mandatory work break, in vehicle scheduling and routing is crucial for safety driving and protecting the interests of drivers. This paper addresses the drop-and-pull container drayage problem with flexible assignment of work break, proposing a mixed-integer programming model and an algorithm for solving realistic-sized instances. Experimental results show the effectiveness of the proposed algorithm in handling vehicle scheduling and routing with work break assignment.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
William N. Caballero, Jose Manuel Camacho, Tahir Ekin, Roi Naveiro
Summary: This research provides a novel probabilistic perspective on the manipulation of hidden Markov model inferences through corrupted data, highlighting the weaknesses of such models under adversarial activity and emphasizing the need for robustification techniques to ensure their security.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Davood Zaman Farsa, Shahryar Rahnamayan, Azam Asilian Bidgoli, H. R. Tizhoosh
Summary: This paper proposes a multi-objective evolutionary framework for compressing feature vectors using deep autoencoders. The framework achieves high classification accuracy and efficient image representation through a bi-level optimization scheme. Experimental results demonstrate the effectiveness and efficiency of the proposed framework in image processing tasks.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Matthew E. Scherer, Raymond R. Hill, Brian J. Lunday, Bruce A. Cox, Edward D. White
Summary: This paper discusses instance generation methods for the multidemand multidimensional knapsack problem and introduces a primal problem instance generator (PPIG) to address feasibility issues in current instance generation methods.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Yin Yuan, Shukai Li, Lixing Yang, Ziyou Gao
Summary: This paper investigates the design of real-time train regulation strategies for urban rail networks to reduce train deviations and passenger waiting times. A mixed-integer nonlinear programming (MINLP) model is used and an efficient iterative optimization (IO) approach is proposed to address the complexity. The generalized Benders decomposition (GBD) technique is also incorporated. Numerical experiments show the effectiveness and computational efficiency of the proposed method.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Xinghai Guo, Netirith Narthsirinth, Weidan Zhang, Yuzhen Hu
Summary: This study proposes a bi-level scheduling method that utilizes unmanned surface vehicles for container transportation. By formulating mission decision and path control models, efficient container transshipment and path planning are achieved. Experimental results demonstrate the effectiveness of the proposed approach in guiding unmanned surface vehicles to complete container transshipment tasks.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Review
Computer Science, Interdisciplinary Applications
Jose-Fernando Camacho-Vallejo, Carlos Corpus, Juan G. Villegas
Summary: This study aims to review the published papers on implementing metaheuristics for solving bilevel problems and performs a bibliometric analysis to track the evolution of this topic. The study provides a detailed description of the components of the proposed metaheuristics and analyzes the common combinations of these components. Additionally, the study provides a detailed classification of how crucial bilevel aspects of the problem are handled in the metaheuristics, along with a discussion of interesting findings.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Xudong Diao, Meng Qiu, Gangyan Xu
Summary: In this study, an optimization model for the design of an electric vehicle-based express service network is proposed, considering limited recharging resources and power management. The proposed method is validated through computational experiments on realistic instances.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Ramon Piedra-de-la-Cuadra, Francisco A. Ortega
Summary: This study proposes a procedure to select candidate sites optimally for ensuring energy autonomy and reinforced service coverage for electric vehicles, while considering demand and budget restrictions.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Danny Blom, Christopher Hojny, Bart Smeulders
Summary: This paper focuses on a robust variant of the kidney exchange program problem with recourse, and proposes a cutting plane method for solving the attacker-defender subproblem. The results show a significant improvement in running time compared to the state-of-the-art, and the method can solve previously unsolved instances. Additionally, a new practical policy for recourse is proposed and its tractability for small to mid-size kidney exchange programs is demonstrated.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Anqi Li, Congying Han, Tiande Guo, Bonan Li
Summary: This study proposes a general framework for designing linear programming instances based on the preset optimal solution, and validates the effectiveness of the framework through experiments.
COMPUTERS & OPERATIONS RESEARCH
(2024)
