Article
Computer Science, Artificial Intelligence
Mostafa Hajiaghaei-Keshteli, Zeynep Cenk, Babek Erdebilli, Yavuz Selim Ozdemir, Fatemeh Gholian-Jouybari
Summary: With limited resources and increasing competition, it is crucial for businesses to make environmentally responsible decisions. That's why they choose to use green and traditional selection criteria to select suppliers. Green Supplier Selection (GSS) involves selecting suppliers based on their environmental performance, leading to reduced environmental impact, improved reputation, compliance with regulations, and cost reduction. This study aims to propose a novel GSS approach for food business packaging operations, using a combination of literature review, criteria determination, and application of the Pythagorean Fuzzy Technique for Order Preference by Similarity to Ideal Solution (PF-TOPSIS) method.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Amandeep Singh, Satish Kumar
Summary: Compared to fuzzy and intuitionistic fuzzy sets, picture fuzzy sets are considered effective tools for decision-making problems. This paper proposes a novel picture fuzzy knowledge measure and derives a new picture fuzzy accuracy measure, demonstrating their performance and validation in applications.
APPLIED SOFT COMPUTING
(2023)
Article
Social Sciences, Interdisciplinary
Haiyang Shang, Fang Su, Serhat Yuksel, Hasan Dincer
Summary: This study aims to identify the primary technical factors for sustainable low-carbon industry by proposing a hybrid multi-criteria decision-making model. The research finds that research and development for renewable sources is of greatest importance for low-carbon industry. The analysis results of fuzzy TOPSIS and fuzzy VIKOR are consistent, suggesting that countries should prioritize research and development investments to minimize the costs of renewable energy problems and attract companies to invest in cleaner energy projects.
Letter
Green & Sustainable Science & Technology
Sayan Mukherjee
Summary: This article provides comments on the paper by Govindan et al. (2013), which introduces a method for evaluating the sustainability performance of suppliers. It suggests using economic, environmental, and social factors for ranking and selecting suppliers, and proposes corrections to some of the equations used in the original study.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Computer Science, Artificial Intelligence
Sanjay Kumar, Asim Gopal Barman
Summary: The study evaluates the environmental performance of suppliers using fuzzy-based multi-criteria decision-making processes, generating overall scores for each alternative through TOPSIS and VIKOR methods. Sensitivity analysis is conducted to analyze the impact of criteria weights on environmental performance.
Article
Environmental Sciences
Asana Hosseini Dolatabad, Jalil Heidary Dahooie, Jurgita Antucheviciene, Mostafa Azari, Seyed Hossein Razavi Hajiagha
Summary: Organizations are increasingly concerned about maintaining their positions in today's changing world and high-tech era due to the emergence of innovative technologies from industrial revolutions. It is believed that achieving competitive advantages based on the trends is crucial for survival and constructive roles. The introduction of Industry 4.0 has significantly impacted enterprises, organizations, and supply chains. Supplier selection is a strategic decision for organizations, as it directly affects profitability, market competition, accountability, product quality, and costs. However, the development of supplier evaluation in the fourth supply chain generation requires further consideration. This study reviews current technologies, methods, and criteria used in previous studies, and proposes a comprehensive methodology for selecting suppliers based on Industry 4.0.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Shio Gai Quek, Harish Garg, Ganeshsree Selvachandran, M. Palanikumar, K. Arulmozhi, Florentin Smarandache
Summary: This article introduces the structure of the (t, s)-regulated interval-valued neutrosophic soft set (abbr. (t, s)-INSS) and proposes a novel distance measure for this model. It also presents the TOPSIS and VIKOR algorithms that work on the (t, s)-INSS. These algorithms are consistent with human intuitions and are versatile in handling heterogeneous data. The (t, s)-INSS model is a conclusive generalization of existing structures and the distance measure is a significant improvement over current measures. The practical implementation of these algorithms in artificial intelligence, especially in the context of the COVID-19 pandemic, is highly valuable. Rating: 8 out of 10.
Article
Automation & Control Systems
Chia-Nan Wang, Thi-Ly Nguyen, Thanh-Tuan Dang
Summary: This paper proposes a hybrid model to determine the most potent green supplier in the steel manufacturing industry in Vietnam. Through expert assessment and ranking, Hoa Phat Group Joint-stock company, Hoa Sen Group, and Pomina Steel Corporation are identified as the top three optimal suppliers.
INTELLIGENT AUTOMATION AND SOFT COMPUTING
(2022)
Article
Operations Research & Management Science
Miguel Ortiz-Barrios, Juan Cabarcas-Reyes, Alessio Ishizaka, Maria Barbati, Natalia Jaramillo-Rueda, Giovani de Jesus Carrascal-Zambrano
Summary: Supplier selection is crucial in the mining sector, impacting various aspects like inventory management, production planning, maintenance scheduling, financial resources, and environment. Decision-makers should consider conflicting criteria and choose a suitable Multi-Criteria Decision Making (MCDM) approach. A combination of powerful MCDM methods is used to select the most suitable supplier, with a case study showing quality criterion as the most crucial aspect.
ANNALS OF OPERATIONS RESEARCH
(2021)
Article
Green & Sustainable Science & Technology
Mohamed Abdel-Basset, Abduallah Gamal, Ripon K. Chakrabortty, Michael J. Ryan
Summary: The demand for energy in Egypt has risen due to economic and societal development, necessitating the use of renewable energy resources. Selecting the most suitable renewable energy systems is a multi-criteria decision-making problem. Research indicates that concentrated solar power is the most suitable renewable energy source for Egypt.
Article
Business
Rajesh Kr Singh, Sachin Kumar Mangla, Manjot Singh Bhatia, Sunil Luthra
Summary: This research presents solutions for the integrated implementation of green and lean practices, with the application of quality control tools, reduction in lead-time, use of right first time approach, and new technology and product innovations being the most crucial for overcoming barriers. The ranking of these solutions will aid managers in making strategic decisions and improving performance in manufacturing firms.
BUSINESS STRATEGY AND THE ENVIRONMENT
(2022)
Article
Multidisciplinary Sciences
Qianlong Zhao, Junyi Chen, Fulun Li, Aishu Li, Qian Li
Summary: The study evaluates the dynamic changes in China's maternal health status from 2004 to 2018, showing an overall improvement in maternal health care year by year, with the best performance from 2015 to 2018. Although the ranking values of various evaluation methods were slightly different, the overall trend was consistent.
Article
Green & Sustainable Science & Technology
Nada A. Nabeeh, Mohamed Abdel-Basset, Gawaher Soliman
Summary: The study validates the impact of the Green Credit Policy (GCP) in China on reducing environmental pollution in manufacturing, and proposes the Neutrosophic Multiple-Criteria Decision-Making Framework (N-MCDMF) to support decision-makers in uncertain environmental conditions and recommend optimal supply chain management alternatives.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Green & Sustainable Science & Technology
Mukesh Kumar, Vikas Kumar Choubey
Summary: The current global economic status quo in the food sector is considered unsustainable. The field of sustainability science is fragmented despite numerous publications. The study develops a methodology for assessing the sustainable performance of food supply chain organizations. The research framework evaluates the sustainability of three Indian dairy firms and provides a fuzzy analytic hierarchy process, fuzzy VIKOR, and fuzzy TOPSIS-based assessment system.
Article
Computer Science, Artificial Intelligence
Jun Zhang, Linze Li, Jing Zhang, Liping Chen, Guojiao Chen
Summary: In recent years, private labels in retail have experienced significant development. Selecting sustainable suppliers for private labels has become a strategic concern for retailers. This study proposes a novel MCDM model for selecting private-label suppliers that comply with sustainability criteria. The model incorporates the Delphi method, an integrated weight algorithm, and a fuzzy set extension in evaluation. The case study highlights the importance of green packaging and labeling, relationship with manufacturing brand, order flexibility, and product traceability in private-label supplier selection.
COMPLEX & INTELLIGENT SYSTEMS
(2023)
Article
Economics
Yuxiang Yang, Shadi Goodarzi, Armin Jabbarzadeh, Behnam Fahimnia
Summary: This paper examines a supply chain with manufacturers and overseas suppliers facing different carbon tax rates and presents an equilibrium decision model for in-house production and outsourcing. Numerical examples analyze the impact of carbon tax rates and consumer's carbon awareness on production and outsourcing decisions, providing important managerial insights and implications for carbon policies.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2022)
Article
Engineering, Industrial
P. Grznar, M. Gregor, A. Gola, I Nielsen, S. Mozol, V Seliga
Summary: Modelling and simulation is a progressive field that can lead to significant financial savings for companies. However, the process of modelling is time-consuming and costly. This article presents a tool designed for quick analysis of the workplace using simulation, aimed at reducing the time needed to create a model and ultimately increasing the productivity of simulation experts.
INTERNATIONAL JOURNAL OF SIMULATION MODELLING
(2022)
Article
Management
Behnam Fahimnia, Meysam Arvan, Tarkan Tan, Enno Siemsen
Summary: Demand planning is influenced by demand forecasts, service level requirements, replenishment constraints, and revenue projections. This research investigates if forecasters recognize the difference between demand forecasts and demand plans, and finds that they factor service levels into their forecasts, even with explicit instructions to predict the most likely demand. This behavior is driven by the service level information and holds true for both students and practitioners.
JOURNAL OF OPERATIONS MANAGEMENT
(2023)
Review
Transportation
Milad Haghani, Rico Merkert, Ali Behnood, Chris De Gruyter, Khashayar Kazemzadeh, Hadi Ghaderi, Zahra Shahhoseini, Vinh Thai, Elnaz Irannezhad, Behnam Fahimnia, S. Travis Waller, David A. Hensher
Summary: In response to the COVID-19 pandemic, scholars have actively addressed its far-reaching societal problems. A new field of transportation science has quickly emerged, focusing on mobility restrictions during the pandemic. This study examines over 400 COVID-19-related studies published in transportation journals between 2020 and 2021, aiming to scope this newly developed research area, outline its diversity, and provide a roadmap for future research. The results show that the COVID-19 segment has developed its own knowledge foundation independent of pre-pandemic studies, and its potential impacts on transportation journals are quantified and discussed.
TRANSPORTATION LETTERS-THE INTERNATIONAL JOURNAL OF TRANSPORTATION RESEARCH
(2023)
Article
Agriculture, Multidisciplinary
Rahim Azadnia, Ali Rajabipour, Bahareh Jamshidi, Mahmoud Omid
Summary: Timely monitoring of apple trees' nutrition status is crucial for accurate nutrient management, and this study aims to establish a cost-effective and non-destructive method for estimating NPK status using Vis/NIR spectroscopy and machine learning. Ground-based sensors provide efficient information on nutritional status, while tissue analysis is laborious and destructive. The results indicate that the developed models using non-linear methods show superior performance in estimating NPK contents in apple tree leaves.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2023)
Article
Computer Science, Artificial Intelligence
Somnath Maji, Kunal Pradhan, Samir Maity, Izabela Ewa Nielsen, Debasis Giri, Manoranjan Maiti
Summary: To meet the requirements of COVID-19 testing, a green corridor system is suggested to transport virus specimens from small hospitals and urban/rural health centers to testing centers. Optimal routing plans are obtained using fixed and variable length genetic algorithms. The objectives of the models are to minimize the system time and the green corridor time while satisfying the 'false negativity' constraint.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Green & Sustainable Science & Technology
T. Mahanth, C. R. Suryasekaran, S. G. Ponnambalam, Bathrinath Sankaranarayanan, Koppiahraj Karuppiah, Izabela Ewa Nielsen
Summary: Due to the increased consumption of electronic items, there has been a significant rise in electronic waste (e-waste), which can have adverse effects. However, this waste also presents an opportunity for value recovery through circular economy (CE) practices. This study identifies and evaluates the barriers to CE practices in e-waste management, categorizing them into social, economic, and environmental factors. A multi-criteria decision-making framework is used to understand the causal interrelationship and rank the barriers. The top five barriers are uncertainty about profitability, insufficient market demand, lack of successful business model, shortage of high-quality recycling materials, and lack of adequate technology. Understanding and prioritizing these barriers can provide valuable insights and guidance for industrial practitioners and policymakers.
Article
Construction & Building Technology
Vihan Weerapura, Ranil Sugathadasa, M. Mavin De Silva, Izabela Nielsen, Amila Thibbotuwawa
Summary: This paper proposes a digital twin (DT) system for the ready-mix concrete (RMC) industry, which serves as a decision support tool for efficient production risk management through predictive maintenance. The system consists of an IoT system, a digital twin operational model, and an advanced analytical dashboard. It provides real-time efficient and interpretable predictive maintenance insights based on anomaly detection, bottleneck identification, process disruption forecast, and cycle time analysis.
Article
Management
Hossein Jahandideh, Kevin McCardle, Christopher Tang, Behnam Fahimnia
Summary: This paper examines a firm's decisions regarding production and sales of age-based products that increase in value over time, such as whisky, wine, and cheese. The firm considers introducing a new product by setting aside some of its production for longer aging. The firm needs to determine if and when to sell different ages of products as partial substitutes. For deterministic and stochastic market size scenarios, the optimal fraction of production reserved for additional aging is analyzed, as well as the effects of deterministic yield loss on the production process.
Article
Thermodynamics
Sara Borhani, Alibakhsh Kasaeian, Peyman Pourmoghadam, Mahmoud Omid
Summary: The goal of this research is to study a trigeneration solar system that can meet household energy demands. A reliable network is trained to forecast the system's functionality under different weather conditions, replacing the time-consuming simulation process. The research shows that warm regions like Ahwaz province have the most suitable weather conditions to effectively utilize the system.
APPLIED THERMAL ENGINEERING
(2023)
Article
Geosciences, Multidisciplinary
Seyed Roohollah Mousavi, Fereydoon Sarmadian, Marcos Esteban Angelini, Patrick Bogaert, Mahmoud Omid
Summary: This study investigates the use of a structural equation modeling (SEM) approach to assess the effects of soil forming factors on key soil properties in an arid and semi-arid region of Iran. The results show that several environmental factors are impacting these soil properties. Although the SEM approach is useful for identifying cause-effect relationships, it is not efficient for digital soil mapping of these soil properties.
Article
Environmental Sciences
Mohammad Hosseinpour-Zarnaq, Mahmoud Omid, Fereydoon Sarmadian, Hassan Ghasemi-Mobtaker
Summary: This research developed a novel deep learning-based model for predicting soil properties using visible and near-infrared spectroscopic data. The study demonstrated that the CNN model outperformed the PLSR model in predicting various soil properties. The use of deep learning-based models and VIS-NIR spectral data was shown to be a feasible method for rapidly assessing important soil properties.
ENVIRONMENTAL EARTH SCIENCES
(2023)
Article
Chemistry, Multidisciplinary
Zbigniew Banaszak, Grzegorz Radzki, Izabela Nielsen, Rasmus Frederiksen, Grzegorz Bocewicz
Summary: This paper presents a declarative model for maintenance logistics in offshore wind farms, enabling online prototyping of wind turbine servicing scenarios using decision-making tools. The model includes factors such as weather-related vessel movement and routing of UAV fleets for maintenance tasks. Case studies focusing on UAV fleet routing and spare parts distribution confirm the feasibility of the model. The open structure of the model allows for easy generalization to support additional functions such as vessel fleet routing, service team planning, and supply chain management.
APPLIED SCIENCES-BASEL
(2023)
Article
Agriculture, Multidisciplinary
Saman Alvandi, Seyed Saeid Mohtasebi, Mahmoud Omid, Mohammad Hosseinpour-Zarnaq
Summary: An intelligent system combining machine vision and artificial neural networks was developed to classify and clean N. sativa seeds and its impurities. The results demonstrated the feasibility of this approach in real-time cleaning and suggested its potential use in detecting, classifying, and automatically cleaning other similar seeds.
SPANISH JOURNAL OF AGRICULTURAL RESEARCH
(2023)
Article
Agriculture, Multidisciplinary
Khaled Mohi-Alden, Mahmoud Omid, Mahmoud Soltani Firouz, Amin Nasiri
Summary: The uniformity of appearance attributes is crucial for bell peppers in order to meet the standards and needs of consumers and the food industry. This research aimed to develop a machine vision-based system for sorting bell peppers based on maturity levels and size, using multilayer perceptron (MLP) artificial neural networks as the nonlinear models. The results showed that the MLP outperformed other models, and the system achieved high accuracy and speed in the in-line sorting process.
INFORMATION PROCESSING IN AGRICULTURE
(2023)
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)
