Article
Computer Science, Information Systems
LeSheng Jin, Zhen-Song Chen, Ronald R. Yager, Tapan Senapati, Radko Mesiar, Diego Garcia Zamora, Bapi Dutta, Luis Martinez
Summary: This study introduces a novel approach to establish OWA operators for basic uncertain information, using problem factorization and integration techniques similar to the Choquet integral. It also discusses various methodologies for determining specific weights to define these operators.
INFORMATION SCIENCES
(2023)
Article
Computer Science, Artificial Intelligence
Juan Baz, Mikel Ferrero-Jaurrieta, Irene Diaz, Susana Montes, Gleb Beliakov, Humberto Bustince
Summary: This paper studies the aggregation of multiple predictors in time series forecasting and introduces a new pre-aggregation extension operator. By examining the behavior and performance of the operator from a probabilistic perspective, its effectiveness is validated in practical examples.
INFORMATION FUSION
(2024)
Article
Engineering, Multidisciplinary
Enseih Kazemi, Danial Sadrian Zadeh, Behzad Moshiri
Summary: This paper proposes a new Minimum Parameter System (MPS) model using Ordered Weighted Averaging (OWA) operators as the data fusion method. By testing different OWA operators, weights for aggregating sensor data were determined, showing high applicability and effectiveness in practical applications.
Article
Computer Science, Theory & Methods
Jesus Medina, Ronald R. Yager
Summary: The paper introduces an extension of OWA operators allowing greater flexibility and the use of different types of OWA operators on the same dataset. Various interesting examples have been studied and a sufficient condition for ensuring the monotonicity of the new flexible operator has been presented.
FUZZY SETS AND SYSTEMS
(2021)
Article
Computer Science, Theory & Methods
Jacek M. Leski
Summary: A new method called Fuzzy Double Ordered C-Regression Models (FDOCRM) is introduced in this paper, which incorporates ordering and fuzzy S-regression estimator to improve method robustness. Large-scale simulations demonstrate the competitiveness and usefulness of the proposed method.
FUZZY SETS AND SYSTEMS
(2023)
Article
Multidisciplinary Sciences
He Jian, Hu Hao, Jiang Haidan, Pan Haize, Liu Chuan
Summary: This study introduced the structure-process-outcome theory to evaluate the redevelopment of brownfield sites. The basic conditions, practice principles, and result orientation of brownfield redevelopment were analyzed, and a three-level evaluation index system was established. To reduce subjectivity, an unbiased scientific evaluation model was constructed. The model was applied to a project in Chengdu, China, and proved to be effective and accurate.
SCIENTIFIC REPORTS
(2023)
Article
Computer Science, Theory & Methods
T. Calvo, P. Fuster-Parra, J. Martin, G. Mayor
Summary: The study emphasizes the importance of consistency in decision-making models. The proposal introduces a special type of extended aggregation functions that ensure the T-S consistency of linearly ordered fuzzy preference relations. Conditions for ensuring consistency in the aggregation process are provided, along with sufficient conditions for the existence of extended aggregation functions that verify T-S consistency. Furthermore, the study establishes the equivalence between T-S consistency and additive consistency for fuzzy preference relations.
FUZZY SETS AND SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Murugan Palanikumar, Krishnan Arulmozhi, Chiranjibe Jana, Madhumangal Pal
Summary: In this article, we discuss fresh approaches to the spherical vague normal set (SVNS) in multiple attribute decision-making (MADM) problems, as well as various operators associated with it. By employing these new approaches, we can find the best option more quickly and obtain more precise and practical conclusions.
Article
Computer Science, Artificial Intelligence
Bo Li, Junqi Ding, Zhengqing Yin, Kaiyu Li, Xue Zhao, Lingxian Zhang
Summary: In this paper, an optimized neural network combined model based on the induced ordered weighted averaging operator is proposed for vegetable price forecasting. The framework integrates the fruit fly algorithm (FOA) with the induced ordered weighted averaging (IWOA) operator. Results show that our model outperforms traditional forecasting models in terms of prediction accuracy and parameter optimization.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Mathematics
Pere Josep Pons-Vives, Mateu Morro-Ribot, Carles Mulet-Forteza, Oscar Valero
Summary: This paper proposes an improved algorithm, OWA-based K-means, for clustering customers based on their spending propensity. Experiments show that the use of OWA operator improves the performance of classical K-means significantly. The OWA-based K-means can be applied to classify customers in different seasons without requiring radical changes in the implementation of the classical method or additional implementation costs in real hotel management.
Article
Computer Science, Artificial Intelligence
Muhammad Akram, Ayesha Bashir
Summary: This paper presents certain quadratic averaging operators in a complex fuzzy mathematical framework, which are used to study various periodic issues and applied in multi-attribute decision-making and wireless target detection. By ranking the aggregated outputs, the best opinion can be chosen and the position and direction of a target can be detected. Additionally, the authors verify the validity and importance of the models through numerical examples.
GRANULAR COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Xiang Li, Zeshui Xu, Hai Wang
Summary: This paper proposes an approach to linguistic three-way decision making problem with double hierarchy linguistic term evaluation information. By defining operational rules and constructing models, combining grey relational analysis and loss functions aggregation method, the decision-making process becomes more scientifically reasonable, and the feasibility of the method is verified in case studies.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2021)
Article
Environmental Sciences
Jiangyue Li, Xi Chen, Alishir Kurban, Tim Van de Voorde, Philippe De Maeyer, Chi Zhang
Summary: This study quantified the spatiotemporal changes of ecosystem services in the major basins of Central Asia and identified conservation priorities using a multi-criterion valuation method. The results showed variations in conservation efficiency among different basins, with ecosystem services being influenced by both natural and socioeconomic factors.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2021)
Article
Biodiversity Conservation
Min Guo, Xin Cong, Hua Zheng, Ming-Juan Zhang, Liang-Jie Wang, Jian-Wen Gong, Shuai Ma
Summary: A well-constructed ecological security pattern (ESP) can promote linkages between ecological sources, mitigate the degradation of ecosystems, and facilitate sustainable urban development. However, previous studies have not adequately considered the trade-offs of ecosystem services when determining ecological sources for ESPs. This research aims to improve the assessment of ESPs by filling this research gap. Through a case study in the Jianghuai Ecological Economic Zone in China, the proposed framework is demonstrated. The results provide insights into improving ecosystem security in other fast-growing cities.
ECOLOGICAL INDICATORS
(2022)
Article
Computer Science, Artificial Intelligence
Martha Flores-Sosa, Ernesto Leon-Castro, Jose M. Merigo, Ronald R. Yager
Summary: This paper introduces the MLR-HOWA operator, which uses HOWA means to obtain beta values. It provides the possibility of under or overestimating results based on the decision maker's expectations and knowledge, allowing for analysis of multiple scenarios from minimum to maximum. The paper also presents the main properties of the operator and two extensions using induced and generalized variables. An application in exchange rate forecasting for five Latin American countries is provided, demonstrating that using different combinations of MLR with OWA operators can reduce forecasting errors.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Management
Konstantinos Petridis, Nikolaos E. Petridis, Ali Emrouznejad, Fouad Ben Abdelaziz
Summary: This paper proposes a two-stage approach for prioritizing volatility models. In the first stage, a novel method is used to rank the models, and in the second stage, the impact of model characteristics on efficiency scores is analyzed.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Hashem Omrani, Meisam Shamsi, Ali Emrouznejad
Summary: This study aims to calculate the scores of technical, social, and environmental efficiency, and introduces a new efficiency called sustainable efficiency. By applying data envelopment analysis models and TOPSIS approach, the overall rankings of airlines in terms of technical, social, environmental, and sustainable efficiencies are obtained.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2023)
Article
Business, Finance
Hashem Omrani, Arash Alizadeh, Ali Emrouznejad, Zeynab Oveysi
Summary: This paper proposes a two-stage DEA model using the best worst method (BWM) to incorporate bank managers' preferences in evaluating bank branches' efficiency. By evaluating Agricultural Bank branches in Iran, the branches are divided into four groups based on their efficiency in each stage and recommendations are provided for each group.
INTERNATIONAL JOURNAL OF FINANCE & ECONOMICS
(2023)
Article
Business
Reza Mahmoudi, Ali Emrouznejad
Summary: The airline industry plays a significant role in the economic development of a country. This study proposes a new game-SBM-NDEA model to evaluate the performance of Decision Making Units (DMUs) with a network structure. The model combines egalitarian bargaining game theory, network data envelopment analysis, and slack-based measure. The model can handle conflicts in the network structure and provide reliable efficiency scores when the number of DMUs is not large enough compared to the inputs and outputs considered. A case study on Iranian domestic airlines from 2013 to 2020 is conducted to analyze their performance and identify possible solutions for improvement.
RESEARCH IN TRANSPORTATION BUSINESS AND MANAGEMENT
(2023)
Article
Operations Research & Management Science
Patanjal Kumar, Sachin Kumar Mangla, Yigit Kazancoglu, Ali Emrouznejad
Summary: Global warming, climate change, and social problems are the most severe human-induced sustainability issues worldwide. This study investigates key factors affecting behavioral and sustainable supply chain coordination in the context of digitization and proposes a new supply chain coordination framework. The results identify environmental performance and decarbonization as the most significant factors and speed to market as the least important factor. Social preferences are found to be a crucial causal factor in resolving coordination issues.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Management
Maria Michali, Ali Emrouznejad, Akram Dehnokhalaji, Ben Clegg
Summary: This paper examines the applicability of the subsampling bootstrap procedure in approximation of the asymptotic distribution of the DEA estimator when the production process has a network structure, and in the presence of undesirable factors. Through Monte Carlo experiments, evidence on the performance of subsampling bootstrap is obtained for two-stage series structures, where overall and stage efficiency estimates are calculated using the additive decomposition approach. The results indicate sensitivity to sample and subsample sizes, as well as the data generating process. Subsampling methodology is then applied to construct confidence interval estimates for railway efficiency scores in 22 European countries.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Operations Research & Management Science
Vincent Charles, Ali Emrouznejad, Tatiana Gherman
Summary: The integration of blockchain and artificial intelligence (AI) in supply chains has attracted considerable attention due to its potential to enhance security, efficiency, and productivity in volatile and complex business environments. This paper reviews the current studies, use cases, and potential research directions for the integration of blockchain and AI in supply chains. The analysis identifies relevant research that contributes to the intellectual wealth and advancement of the supply chain discipline.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Hashem Omrani, Meisam Shamsi, Ali Emrouznejad, Tamara Teplova
Summary: Conventional Data Envelopment Analysis (DEA) lacks the ability to evaluate Decision-Making Units (DMUs) in vast industries like banks with only one type of efficiency and uncertain data. In this paper, a multi-objective DEA model is proposed to calculate three types of efficiencies for bank branches under uncertain data. The model employs a modified DEA model, a robust approach to handle uncertainty, and a fuzzy programming method to convert the multi-objective model into a single-objective one. The results from a real case study of 45 Agriculture bank branches in Iran validate the accuracy of the proposed model and enable a comparative analysis to identify benchmark and inefficient branches.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Editorial Material
Management
Ali Emrouznejad, Gholam R. Amin
IMA JOURNAL OF MANAGEMENT MATHEMATICS
(2023)
Article
Management
Ali Emrouznejad, Marianna Marra, Guo-Liang Yang, Maria Michali
Summary: We present the latest advances in eco-efficiency measurement using data envelopment analysis and Malmquist-Luenberger productivity index. We also address productivity change over time and provide policy suggestions for reducing CO2 emissions. Our literature review, based on 311 papers published between 1989 and 2022, includes network analysis of citations to illustrate the evolution of research in this field.
IMA JOURNAL OF MANAGEMENT MATHEMATICS
(2023)
Article
Management
Ali Emrouznejad, Gholam R. Amin, Mojtaba Ghiyasi, Maria Michali
Summary: Data envelopment analysis (DEA) is a mathematical programming approach used to assess the efficiency of decision-making units (DMUs) in various sectors. Inverse DEA is a post-DEA sensitivity analysis approach that aims to determine the optimal quantity of inputs and/or outputs for each DMU under input and/or output perturbation to achieve a given efficiency target.
IMA JOURNAL OF MANAGEMENT MATHEMATICS
(2023)
Editorial Material
Operations Research & Management Science
Ali Emrouznejad, Soumyadeb Chowdhury, Prasanta Kumar Dey
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Bei Hong, Jing Liu, Lijun Shen, Qiwei Xie, Jingbin Yuan, Ali Emrouznejad, Hua Han
Summary: We present a novel neuron reconstruction framework that combines a global optimization goal with biologically inspired priors. This framework includes 3D instances of synapses and mitochondria as constraints to incorporate non-local connectivity information in neuron segmentation. We design a flexible decision procedure to handle the potential influence of upstream ultrastructure error. Comparative studies on public datasets demonstrate significant improvements over existing hierarchical agglomeration algorithms through the decision of ultrastructural connectivity constraints.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Management
Chuanjin Zhu, Nan Zhu, Ali Emrouznejad, Tao Ye
Summary: This study extends the Malmquist productivity index by using non-parametric mathematical modeling of production processes. The index is applicable to the joint production of desirable and undesirable outputs and can provide intuitive explanations for productivity changes over time. As a practical benchmarking tool, it offers valuable information for managerial decision-making.
IMA JOURNAL OF MANAGEMENT MATHEMATICS
(2023)
Article
Economics
Xiao Shi, Libo Wang, Ali Emrouznejad
Summary: This study proposes an improved slacks-based measure model with undesirable outputs, which splits bank efficiency into two parallel stages, enabling the identification of overall inefficiency sources and capturing the efficiency differences between different cost types. Empirical results show that the changes in overall bank efficiency are mainly driven by the changes in the second stage. This method provides valuable information for decision making.
SOCIO-ECONOMIC PLANNING SCIENCES
(2023)
