Article
Computer Science, Artificial Intelligence
Mojtaba Ashour, Amir Mahdiyar
Summary: Analytic Hierarchy Process (AHP) is a widely applied technique in multi-criteria decision-making problems, but the sheer number of AHP methods presents challenges for scholars and practitioners in selecting the most suitable method. This paper reviews articles published between 2010 and 2023 proposing hybrid, improved, or modified AHP methods, classifies them based on their contributions, and provides a comprehensive summary table and roadmap to guide the method selection process.
APPLIED SOFT COMPUTING
(2024)
Article
Green & Sustainable Science & Technology
Margarida Rodrigues, Mario Franco
Summary: Facing global climate change, transitioning to a green economy is crucial. This study focused on how small and medium-sized enterprises (SMEs) engage in green innovation activities. Through qualitative case study approach and interviews with three SME owners/managers, it was found that green innovation is a concern for managers, but its implementation is challenging. Two of the SMEs only implemented waste recycling measures, indicating a need for a more comprehensive shift towards a green and sustainable business model. The urgency for SMEs to adopt sustainable practices and understand the importance of green innovation is highlighted.
Article
Engineering, Marine
H. Diaz, A. P. Teixeira, C. Guedes Soares
Summary: A Monte Carlo simulation procedure is developed to select the optimum location of wind farms by combining major decision criteria and subjective judgments from decision-makers. The method utilizes Monte Carlo simulation, conventional Analytic Hierarchy Process, and Fuzzy Analytic Hierarchy Process. It is applied to offshore wind farms in Spain to rank the most suitable turbine positioning locations.
Article
Computer Science, Information Systems
Phi-Hung Nguyen
Summary: The outbreak of COVID-19 has had a significant impact on the global economy, particularly on the agricultural supply chains in developing and third world countries. This study assessed the critical risks associated with these supply chains and identified transportation, market, and policy as the most important factors in mitigating the risks.
CMC-COMPUTERS MATERIALS & CONTINUA
(2022)
Article
Green & Sustainable Science & Technology
Syamsari Syamsari, Muhammad Ramaditya, Irma Andriani, Ayu Puspitasari
Summary: This study aims to develop a strategic policy for micro, small, and medium enterprises to deal with disruptions and maintain sustainability. The government intervention is essential to strengthen the resilience of enterprises. Using a holistic approach, the study identified the prioritized factors, actors, goals, and strategies in formulating a policy strategy for the sustainability system in Takalar Regency.
Article
Automation & Control Systems
Xiaofeng Chen, Yanting Fang, Junyi Chai, Zeshui Xu
Summary: This paper investigates the integration of intuitionistic fuzzy (IF) sets and Analytical Hierarchy Process (AHP) to maximize advantages. Quantitative differences between AHP weights and normalized defuzzified IF-AHP weights are illustrated, revealing qualitative and quantitative disparities between AHP and IF-AHP. The study identifies conditions and strategies for utilizing IF-AHP over AHP, with data experiments and case studies for validation.
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2022)
Article
Chemistry, Multidisciplinary
Ghasan Alfalah, Munther Al-Shalwi, Nehal Elshaboury, Abobakr Al-Sakkaf, Othman Alshamrani, Altyeb Qassim
Summary: Fires pose significant risks to life, property, and the economy. Traditional fire safety assessment methods are laborious and challenging, hindering the identification of fire hazards and optimal safety measures. This research introduces an analytic hierarchy process for assessing building fire safety, supported by case studies that demonstrate its superiority over conventional techniques. The proposed method provides hazard and safety ratings, yielding comprehensible and comparable results, making it a valuable decision-making tool for enhancing fire safety in buildings.
APPLIED SCIENCES-BASEL
(2023)
Article
Fisheries
Nishan Raja Raja, Nila Rekha Peter, Sandeep Kizhakkekarammal Puthiyedathu, Chandrasekar Vasudevan, Soumyabrata Sarkar, Albin Sunny
Summary: Cage farming is becoming popular in brackishwater resources in India, and this study aims to locate suitable cage farming sites in the Muttukadu brackishwater ecosystem. By considering water quality, environmental factors, and accessibility, the study used the fuzzy analytic hierarchy process to identify potential areas for cage farming development.
AQUACULTURE INTERNATIONAL
(2023)
Article
Computer Science, Information Systems
Nursah Alkan, Cengiz Kahraman
Summary: Innovations in digital technology have a significant impact on the supply chain and logistics sectors. The concept of a digital supply chain has emerged as a new trend in manufacturing and services. However, organizations face uncertainties in adapting to digitalization and prioritizing criteria and strategies. To address these challenges, the study proposes a new method called the interval-valued fermatean fuzzy analytic hierarchy process (IVFF-AHP). This method helps determine the best strategy and criteria for digital transformation in the supply chain.
Review
Mathematics
Sangeeta Pant, Anuj Kumar, Mangey Ram, Yury Klochkov, Hitesh Kumar Sharma
Summary: This article provides a brief review of the consistency measures in AHP and the functional relationships among different consistency indices. It also offers some thoughtful research directions for further development and improvement of AHP.
Article
Public, Environmental & Occupational Health
Shiqian Wang, Lin Li, Yanjun Jin, Rui Liao, Yen-Ching Chuang, Zhong Zhu
Summary: A model was developed to evaluate and identify key factors contributing to burnout in orthopedic surgeons, providing guidance for managing burnout in hospitals. The model used the analytic hierarchy process (AHP) with 3 dimensions and 10 sub-criteria based on literature review and expert assessment. Expert and purposive sampling was conducted, and 17 orthopedic surgeons were selected as research subjects. The results showed that the personal/family dimension was the key factor affecting burnout, with the top four sub-criteria being little time for family, anxiety about clinical competence, work-family conflict, and heavy work load.
INTERNATIONAL JOURNAL OF PUBLIC HEALTH
(2023)
Article
Engineering, Industrial
Sharaf AlKheder, Hajar Al Otaibi, Zahra Al Baghli, Shaikhah Al Ajmi, Mohammad Alkhedher
Summary: The construction of megaprojects is crucial for the development and economic growth of any country, especially in developing nations. However, megaprojects in Kuwait face restrictions that hinder their execution and lead to significant delays. This study aims to develop a complexity measurement model for megaprojects in Kuwait, focusing on the New Kuwait University campus as a case study. The study applies a hybrid fuzzy analytic hierarchy process (FAHP) method and compares it with the conventional AHP method. The findings reveal the complexity factors and their varying levels in different dimensions, emphasizing the importance of assessing and understanding these complexities for the successful completion of megaprojects.
ENGINEERING CONSTRUCTION AND ARCHITECTURAL MANAGEMENT
(2023)
Article
Mathematics
Svajone Bekesiene, Aidas Vasilis Vasiliauskas, Sarka Hoskova-Mayerova, Virgilija Vasiliene-Vasiliauskiene
Summary: This paper presents the application of Fuzzy AHP-TOPSIS hybrid method in distance learning quality assessment surveys. Thirty-four judges with specific knowledge and skills were chosen to evaluate three alternatives by fourteen criteria, and statistical analysis was used to process the data. The study further provides useful guidelines for the development of an easily understandable hierarchy of criteria model reflecting the main goal of study quality assessment.
Article
Mathematics
Chin-Yi Chen, Jih-Jeng Huang
Summary: This paper presents an innovative method that integrates dynamic Bayesian networks (DBNs) with the analytic hierarchy process (AHP) to model dynamic interdependencies between criteria in multi-criteria decision-making (MCDM) problems. The proposed method extends the AHP to accommodate time-dependent issues and reduces to the conventional AHP when ignoring specific information, making it a more general AHP model.
Article
Computer Science, Theory & Methods
M. H. Mohammed Hitham, Hatem Elkadi, Neamat El Tazi
Summary: This study collects elements from a wide range of literature and identifies the most relevant elements through expert survey. The weights for these elements are determined using multi-criteria decision-making techniques, and the fuzzy AHP method is applied to address uncertainty and prioritize the dimensions and sub-dimensions for digital transformation implementation.
INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS
(2023)
Article
Economics
Patrick B. M. Fahim, Manuel Martinez de Ubago Alvarez de Sotomayor, Jafar Rezaei, Arjan van Binsbergen, Michiel Nijdam, Lorant Tavasszy
Summary: The Physical Internet is a vision for the future global freight transport and logistics system, aiming to improve efficiency and sustainability. The role of maritime ports in the context of the Physical Internet is still underexplored. Global governance of FTL systems is critical for the pace of development and adoption.
Article
Business
Halit Duran, Serdal Temel, Victor Scholten
Summary: This study aims to identify the drivers and barriers for new product development (NPD) success in an emerging economy setting, specifically in Turkey. The results suggest that internal capabilities and close relationships with local customers are crucial for NPD success in emerging economies. Government officials in emerging economies should be cautious with informal actions that could disrupt the investment and innovation environment.
INTERNATIONAL JOURNAL OF INNOVATION SCIENCE
(2022)
Article
Psychology, Applied
Jafar Rezaei, Alireza Arab, Mohammadreza Mehregan
Summary: This study examines the equalizing bias in various MADM methods, finding that AHP and BWM have less equalizing bias compared to SMART, Swing, and PA. Additionally, hierarchical problem structuring leads to a reduction in equalizing bias across all methods, though the reduction varies significantly among the methods. These findings validate debiasing strategies proposed in existing literature and can be useful for decision-makers and researchers in selecting and developing new decision-making methods.
JOURNAL OF BEHAVIORAL DECISION MAKING
(2022)
Article
Engineering, Civil
Ali Nadi, Alex Nugteren, Maaike Snelder, J. W. C. Van Lint, Jafar Rezaei
Summary: This paper introduces an advisory-based time slot management system to control truck arrivals at seaport terminals and reduce congestion. The proposed modeling framework uses discrete choice modeling to infer truck arrival preferences. Through simulation evaluation, the effectiveness of the designed system is demonstrated.
TRANSPORTATION RESEARCH RECORD
(2022)
Article
Business
Fabian de Prieelle, Mark de Reuver, Jafar Rezaei
Summary: This article examines the relative importance of ecosystem data governance as an adoption factor for IoT data sharing platforms. The study finds that businesses consider a variety of factors equally important, with ecosystem data governance ranking in the middle range. Factors like benefits and readiness are considered the most important. However, among the adoption factors that platform providers can control directly, ecosystem data governance ranks among the highest. These findings are important for guiding data platform operators in designing strategies to attract data owners.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2022)
Article
Business
Hanieh Khodaei, Victor E. Scholten, Emiel F. M. Wubben, S. W. F. (Onno) Omta
Summary: This study examines the critical support activities provided by academic spin-off facilitators to high-tech academic spin-offs, such as business support, business plan development, legal support, and network support. The findings highlight the importance of these activities in facilitating the growth and market reach of spin-offs.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2022)
Article
Management
Yingying Liang, Yanbing Ju, Yan Tu, Jafar Rezaei
Summary: This study presents a nonadditive BWM method that considers interactions between criteria, using the Choquet integral. It introduces a nonlinear optimization model to minimize the deviation of obtained weights from pairwise comparisons, taking into account the criterion interactions. A linear variant of the nonadditive BWM is also discussed. The applicability of the proposed approach is demonstrated through a real-world case study.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2023)
Article
Management
Jafar Rezaei, Alireza Arab, Mohammadreza Mehregan
Summary: This study examines the existence of anchoring bias in two multi-attribute decision-making methods - simple multi-attribute rating technique (SMART) and Swing. The results show that these methods, which have different starting points, display different degrees of anchoring bias. However, both methods tend to overweigh the less important attributes and underweigh the more important attributes. The study also suggests that the best-worst method (BWM), which has two opposite anchors, can produce results that are less prone to anchoring bias.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2022)
Article
Transportation
Patrick B. M. Fahim, Gerjan Mientjes, Jafar Rezaei, Arjan van Binsbergen, Benoit Montreuil, Lorant Tavasszy
Summary: The Physical Internet is a paradigm-changing vision that is expected to significantly impact the freight transport and logistics system. However, the uncertainty associated with its development creates challenges for current stakeholders, including ports. This study addresses the lack of research on port policy under uncertain developments towards the Physical Internet by providing insights and recommendations through scenario analysis and multi-criteria decision analysis.
MARITIME POLICY & MANAGEMENT
(2023)
Article
Engineering, Industrial
Kailan Wu, Bart De Schutter, Jafar Rezaei, Lorant Tavasszy
Summary: Consumer goods supply chains are striving to develop and offer green products to capture new business opportunities and improve profitability. The paper focuses on marginal and development cost-intensive green products (MDIGPs) like electric vehicles, examining the challenges of designing these products within the context of demand uncertainty. The study formulates a game-theoretic framework and proposes a bargaining game to coordinate decisions, finding that demand uncertainty can impact product greenness and prices in unexpected ways.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE-OPERATIONS & LOGISTICS
(2023)
Article
Management
Majid Mohammadi, Jafar Rezaei
Summary: This paper presents a new multi-criteria decision-making method called the ratio product model (RPM) and compares it with the weighted sum model (WSM) and the weighted product model (WPM). The RPM addresses the issues of the WSM and WPM by considering performance scores and criteria weights as compositions. Examples demonstrate that the RPM leads to reliable conclusions while the WSM and WPM may result in erroneous conclusions. The proposed method is a significant contribution to the field of MCDM and provides a correct way to analyze decision problems respecting the nature and constraints of the input data.
JOURNAL OF MULTI-CRITERIA DECISION ANALYSIS
(2023)
Article
Engineering, Industrial
Mansoor Davoodi, Jafar Rezaei
Summary: This study presents a general framework, called Bi-sided facility location, for solving a wide range of combined facility location and routing problems. The framework focuses on improving the service quality on the client-side and the interconnection quality and eligibility on the center-side. The study proposes a heuristic approximation algorithm that utilizes geometric objects and algorithms to find approximation Pareto-optimal solutions.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE-OPERATIONS & LOGISTICS
(2023)
Article
Operations Research & Management Science
Jafar Rezaei, Milosz Kadzinski, Chrysoula Vana, Lori Tavasszy
Summary: This paper proposes a method to incorporate environmental evaluation criteria into supplier segmentation, analyzing the green potential of suppliers by evaluating their capabilities and willingness, and using a sorting method to solve the multi-criteria decision-making problem. It also introduces a simple method to assess the carbon footprint of the raw materials supplied by the suppliers, and combines the assessment results with the segmentation for a more useful classification.
ANNALS OF OPERATIONS RESEARCH
(2022)
Proceedings Paper
Management
Jafar Rezaei
Summary: The Best-Worst Method (BWM) is a multi-criteria decision-making method that uses pairwise comparisons to determine the relative importance of criteria. Unlike other methods, BWM uses two reference points to eliminate anchoring bias, resulting in more reliable results.
ADVANCES IN BEST-WORST METHOD, BWM2021
(2022)
Article
Management
Alexander T. C. Onstein, Lorant A. Tavasszy, Jafar Rezaei, Dick A. van Damme, Adeline Heitz
Summary: This paper studies the factors that drive distribution structure design (DSD) and develops a sector-neutral framework that can support decision-makers and regional policy-makers in their decision-making process and spatial planning.
INTERNATIONAL JOURNAL OF LOGISTICS-RESEARCH AND APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Jin Zhang, Zekang Bian, Shitong Wang
Summary: This study proposes a novel style linear k-nearest neighbor method to extract stylistic features using matrix expressions and improve the generalizability of the predictor through style membership vectors.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Qifeng Wan, Xuanhua Xu, Jing Han
Summary: In this study, we propose an innovative approach for dimensionality reduction in large-scale group decision-making scenarios that targets linguistic preferences. The method combines TF-IDF feature similarity and information loss entropy to address challenges in decision-making with a large number of decision makers.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Hegui Zhu, Yuchen Ren, Chong Liu, Xiaoyan Sui, Libo Zhang
Summary: This paper proposes an adversarial attack method based on frequency information, which optimizes the imperceptibility and transferability of adversarial examples in white-box and black-box scenarios respectively. Experimental results validate the superiority of the proposed method and its application in real-world online model evaluation reveals their vulnerability.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Jing Tang, Xinwang Liu, Weizhong Wang
Summary: This paper proposes a hybrid generalized TODIM approach in the Fine-Kinney framework to evaluate occupational health and safety hazards. The approach integrates CRP, dynamic SIN, and PLTSs to handle opinion interactions and incomplete opinions among decision makers. The efficiency and rationality of the proposed approach are demonstrated through a numerical example, comparison, and sensitivity studies.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Shigen Shen, Chenpeng Cai, Zhenwei Li, Yizhou Shen, Guowen Wu, Shui Yu
Summary: To address the damage caused by zero-day attacks on SIoT systems, researchers propose a heuristic learning intrusion detection system named DQN-HIDS. By integrating Deep Q-Networks (DQN) into the system, DQN-HIDS gradually improves its ability to identify malicious traffic and reduces resource workloads. Experiments demonstrate the superior performance of DQN-HIDS in terms of workload, delayed sample queue, rewards, and classifier accuracy.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Song Deng, Qianliang Li, Renjie Dai, Siming Wei, Di Wu, Yi He, Xindong Wu
Summary: In this paper, we propose a Chinese text classification algorithm based on deep active learning for the power system, which addresses the challenge of specialized text classification. By applying a hierarchical confidence strategy, our model achieves higher classification accuracy with fewer labeled training data.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Kaan Deveci, Onder Guler
Summary: This study proves the lack of robustness in nonlinear IF distance functions for ranking intuitionistic fuzzy sets (IFS) and proposes an alternative ranking method based on hypervolume metric. Additionally, the suggested method is extended as a new multi-criteria decision making method called HEART, which is applied to evaluate Turkey's energy alternatives.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Fu-Wing Yu, Wai-Tung Ho, Chak-Fung Jeff Wong
Summary: This research aims to enhance the energy management in commercial building air-conditioning systems, specifically focusing on chillers. Ridge regression is found to outperform lasso and elastic net regression when optimized with the appropriate hyperparameter, making it the most suitable method for modeling the system coefficient of performance (SCOP). The key variables that strongly influence SCOP include part load ratios, the operating numbers of chillers and pumps, and the temperatures of chilled water and condenser water. Additionally, July is identified as the month with the highest potential for performance improvement. This study introduces a novel approach that balances feature selection, model accuracy, and optimal tuning of hyperparameters, highlighting the significance of a generic and simplified chiller system model in evaluating energy management opportunities for sustainable operation. The findings from this research can guide future efforts towards more energy-efficient and sustainable operations in commercial buildings.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Xiaoyan Chen, Yilin Sun, Qiuju Zhang, Xuesong Dai, Shen Tian, Yongxin Guo
Summary: In this study, a method for dynamically non-destructive grasping of thin-skinned fruits is proposed. It utilizes a multi-modal depth fusion convolutional neural network for image processing and segmentation, and combines the evaluation mechanism of optimal grasping stability and the forward-looking non-destructive grasp control algorithm. The proposed method greatly improves the comprehensive performance of grasping delicate fruits using flexible hands.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Yuxuan Yang, Siyuan Zhou, He Weng, Dongjing Wang, Xin Zhang, Dongjin Yu, Shuiguang Deng
Summary: The study proposes a novel model, POIGDE, which addresses the challenges of data sparsity and elusive motives by solving graph differential equations to capture continuous variation of users' interests. The model learns interest transference dynamics using a time-serial graph and an interval-aware attention mechanism, and applies Siamese learning to directly learn from label representations for predicting future POI visits. The model outperforms state-of-the-art models on real-world datasets, showing potential in the POI recommendation domain.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
S. Karthika, P. Rathika
Summary: The widespread development of monitoring devices in the power system has generated a large amount of power consumption data. Storing and transmitting this data has become a significant challenge. This paper proposes an adaptive data compression algorithm based on the discrete wavelet transform (DWT) for power system applications. It utilizes multi-objective particle swarm optimization (MO-PSO) to select the optimal threshold. The algorithm has been tested and outperforms other existing algorithms.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Jiaqi Guo, Haiyan Wu, Xiaolei Chen, Weiguo Lin
Summary: In this study, an adaptive SV-Borderline SMOTE-SVM algorithm is proposed to address the challenge of imbalanced data classification. The algorithm maps the data into kernel space using SVM and identifies support vectors, then generates new samples based on the neighbors of these support vectors. Extensive experiments show that this method is more effective than other approaches in imbalanced data classification.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Qiumei Zheng, Linkang Xu, Fenghua Wang, Yongqi Xu, Chao Lin, Guoqiang Zhang
Summary: This paper proposes a new semantic segmentation network model called HilbertSCNet, which combines the Hilbert curve traversal and the dual pathway idea to design a new spatial computation module to address the problem of loss of information for small targets in high-resolution images. The experiments show that the proposed network performs well in the segmentation of small targets in high-resolution maps such as drone aerial photography.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Mojtaba Ashour, Amir Mahdiyar
Summary: Analytic Hierarchy Process (AHP) is a widely applied technique in multi-criteria decision-making problems, but the sheer number of AHP methods presents challenges for scholars and practitioners in selecting the most suitable method. This paper reviews articles published between 2010 and 2023 proposing hybrid, improved, or modified AHP methods, classifies them based on their contributions, and provides a comprehensive summary table and roadmap to guide the method selection process.
APPLIED SOFT COMPUTING
(2024)
Review
Computer Science, Artificial Intelligence
Gerardo Humberto Valencia-Rivera, Maria Torcoroma Benavides-Robles, Alonso Vela Morales, Ivan Amaya, Jorge M. Cruz-Duarte, Jose Carlos Ortiz-Bayliss, Juan Gabriel Avina-Cervantes
Summary: Electric power system applications are complex optimization problems. Most literature reviews focus on studying electrical paradigms using different optimization techniques, but there is a lack of review on Metaheuristics (MHs) in these applications. Our work provides an overview of the paradigms underlying such applications and analyzes the most commonly used MHs and their search operators. We also discover a strong synergy between the Renewable Energies paradigm and other paradigms, and a significant interest in Load-Forecasting optimization problems. Based on our findings, we provide helpful recommendations for current challenges and potential research paths to support further development in this field.
APPLIED SOFT COMPUTING
(2024)
