Article
Operations Research & Management Science
Mohammad Izadikhah, Elnaz Azadi, Majid Azadi, Reza Farzipoor Saen, Mehdi Toloo
Summary: This paper introduces a practical technique, network data envelopment analysis (NDEA), for assessing the performance of sustainable supply chain management (SSCM). A new NDEA model is proposed to evaluate the efficiency of SSCM under uncertain conditions. The efficacy of the proposed method is demonstrated through a case study in the soft drinks industry.
ANNALS OF OPERATIONS RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Maryam Shadab, Saber Saati, Reza Farzipoor Saen, Mohammad Khoveyni, Amin Mostafaee
Summary: Research focuses on efficiency and performance issues in sustainable supply chains, identifying congestion of intermediate products as a key factor in reducing efficiency. The study explores the use of Data Envelopment Analysis (DEA) to detect congestion and proposes Network DEA (NDEA) models for analysis.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Business
Majid Azadi, Saeed Yousefi, Reza Farzipoor Saen, Hadi Shabanpour, Fauzia Jabeen
Summary: The study proposes a network data envelopment analysis (NDEA) model and a deep learning approach for predicting the sustainability of healthcare supply chains (HSCs). Technological advances such as deep learning, artificial intelligence (AI), and Blockchain have gained importance in HSCs and are seen as competitive advantages. The use of advanced performance evaluation techniques, including DEA, has garnered considerable attention in enhancing HSCs' performance. The results highlight the top-ranking HSCs that utilize fewer facilities, have desirable outputs, and minimal undesirable outputs.
JOURNAL OF BUSINESS RESEARCH
(2023)
Article
Operations Research & Management Science
Javad Gerami, Reza Kiani Mavi, Reza Farzipoor Saen, Neda Kiani Mavi
Summary: Assessing the efficiency of a supply chain is crucial for managers and decision makers. This paper introduces a network data envelopment analysis model to evaluate the performance of supply chains. By incorporating ratio data into the evaluation, important information can be conveyed to managers. The applicability of the proposed model is demonstrated through the assessment of 19 hospitals in Iran.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Elnaz Azadi, Zohreh Moghaddas, Reza Farzipoor Saen, Abbas Mardani, Majid Azadi
Summary: Supply chains are complex systems that involve interactions, components, and flows. The rise of green supply chains has prompted policymakers and managers to consider environmental factors alongside the economic aspect. However, current models struggle to evaluate the performance of green supply chains in an integrated manner. To address this issue, this paper proposes a network data envelopment analysis (NDEA) method as an effective approach for evaluating green supply chains.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Management
Richard Kraude, Sriram Narayanan, Srinivas Talluri
Summary: This paper constructs a network data envelopment analysis (NDEA) model to assess risk mitigation investments in the supply chain, providing a more holistic and useful evaluation by considering the cost of strategies, performance outcomes, and interdependencies among different stages.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Management
Zohreh Sadeghi, Reza Farzipoor Saen, Mahdi Moradzadehfard
Summary: This article presents a new model for evaluating sustainable supply chain performance, which provides valid and reliable results by using sustainability accounting information and handling non-positive data.
OPERATIONS MANAGEMENT RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Haniye Moazeni, Behrouz Arbab Shirani, Seyed Reza Hejazi
Summary: This study explores the production and supply networks, as well as the demand allocation in Iran's stone industry. It proposes a public-private partnership model based on a win-win approach to enhance export opportunities and improve production efficiency. The study utilizes network data envelopment analysis and a game theoretic framework to evaluate the efficiency of each industrial unit in the network. The findings show that the proposed model leads to a significant increase in profits from customer demands.
JOURNAL OF COMPUTATIONAL SCIENCE
(2022)
Article
Management
B. C. Giri, C. H. Glock
Summary: This study examines the bullwhip effect in a manufacturing/remanufacturing supply chain and finds that it may occur at each echelon depending on the values of the autoregressive and moving average parameters of the demand process. The study also investigates the effects of remanufacturing yield, variance of market shock on price, and lead times on the bullwhip effect.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Operations Research & Management Science
Majid Azadi, T. C. E. Cheng, Reza Kazemi Matin, Reza Farzipoor Saen
Summary: This research develops a network data envelopment analysis model to assess the resilience and sustainability of healthcare supply chains (SCs) in response to the COVID-19 pandemic outbreak. The proposed model can handle different types of data and introduces a modified directional distance function for efficiency measurement. The performance of 28 healthcare SCs is evaluated to demonstrate the applicability and capability of the approach.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Operations Research & Management Science
Hossein Hajaji, Sara Yousefi, Reza Farzipoor Saen, Amir Hassanzadeh
Summary: The adaptive network DEA model evaluates the overall and divisional efficiency of supply chains, taking into account managerial and natural disposability, and suggests new investment opportunities under congestion type.
RAIRO-OPERATIONS RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Robabeh Eslami, Mohammad Khoveyni
Summary: This study introduces a novel enhanced Russell graph (ERG) efficiency measure for evaluating the efficiency score of multi-stage decision-making units (DMUs). The proposed model is extended to general multi-stage series network structures. Two numerical and empirical examples are provided to illustrate the use of the proposed model and the managerial and economic implications of measuring the efficiency score of multi-stage DMUs.
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
(2022)
Article
Management
Reza Farzipoor Saen, Mohammad Izadikhah
Summary: This study develops a new network data envelopment analysis model and an interval network directional distance function of inefficiency model to assess the sustainability of supply chains. The results show that the activities in the Making Division have the highest effect on the whole network structure.
OPERATIONS MANAGEMENT RESEARCH
(2022)
Article
Economics
Farhad Hosseinzadeh Lotfi, Reza Farzipoor Saen, Zohreh Moghaddas, Mohsen Vaez-Ghasemi
Summary: Desirable and undesirable outputs are produced together in most production activities, and they are interdependent. Reducing undesirable outputs may lead to a decrease in desirable ones as well. This study introduces and applies concepts and models to assess the sustainability of supply chains, considering the dependency between desirable and undesirable outputs in an SBM network system. A new network data envelopment analysis (NDEA) model based on the Slack Based Model (SBM) is developed, and a case study on wheat supply chains is presented to demonstrate various aspects of the proposed model, which considers both types of outputs.
SOCIO-ECONOMIC PLANNING SCIENCES
(2023)
Article
Green & Sustainable Science & Technology
Reza Farzipoor Saen, Balal Karimi, Amirali Fathi
Summary: This paper discusses the importance of sustainable supply chain management in the transport industry and proposes a Malmquist productivity index based on network data envelopment analysis model to evaluate the sustainability of intercity passenger transportation.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Operations Research & Management Science
Javad Gerami, Reza Kiani Mavi, Reza Farzipoor Saen, Neda Kiani Mavi
Summary: Assessing the efficiency of a supply chain is crucial for managers and decision makers. This paper introduces a network data envelopment analysis model to evaluate the performance of supply chains. By incorporating ratio data into the evaluation, important information can be conveyed to managers. The applicability of the proposed model is demonstrated through the assessment of 19 hospitals in Iran.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Operations Research & Management Science
Mohammad Izadikhah, Reza Farzipoor Saen
Summary: This study presents a new stochastic two-stage DEA model for assessing the sustainability of supply chains. Unlike conventional models, this model considers intermediate products. The efficacy of the model is demonstrated through a case study.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Engineering, Industrial
Majid Azadi, Zohreh Moghaddas, T. C. E. Cheng, Reza Farzipoor Saen
Summary: Evaluating the performance of providers of Industry 4.0 technologies is a ongoing challenge, and existing methods have some shortcomings. In this study, we propose a comprehensive analytical method based on data envelopment analysis to assess the sustainability of cloud service providers for Industry 4.0.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Operations Research & Management Science
Majid Azadi, Zohreh Moghaddas, Reza Farzipoor Saen, Angappa Gunasekaran, Sachin Kumar Mangla, Alessio Ishizaka
Summary: This paper develops a network range directional measure approach to evaluate the sustainability and resilience of healthcare supply chains in response to the COVID-19 pandemic outbreak. Advanced management science and operations research methods can improve the efficiency of healthcare systems. The proposed approach can handle different types of data and provides guidance for improving the efficiency of healthcare supply chains.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Operations Research & Management Science
Hamid Kiaei, Reza Farzipoor Saen, Reza Kazemi Matin
Summary: In this study, Network Data Envelopment Analysis models are used to identify more sources of inefficiency by considering the internal structure of production units. The aim is to assess and improve the performance of Decision Making Units using a two-stage network and a cross-efficiency approach. The main contributions include a new benevolent method in cross-efficiency evaluation and a method for setting inputs and outputs target to improve cross-evaluations.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Operations Research & Management Science
Mohammad Tavassoli, Reza Farzipoor Saen
Summary: This study proposes a novel non-radial fuzzy network data envelopment analysis (FNDEA) model for assessing the sustainability of Iranian Combined Cycle Power Plants (ICCPPs) in a fuzzy context. The proposed model can simultaneously evaluate the sustainability, operational performance, and environmental performance of ICCPPs. The results reveal that 46% of ICCPPs have a relatively good performance in terms of operational and environmental performance. Furthermore, the correlation coefficient among different types of efficiency scores highlights the significant impact of environmental efficiency on the overall efficiency of ICCPPs. Finally, suggestions to improve the sustainability of ICCPPs are provided.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Saeed Yousefi, Hadi Shabanpour, Kian Ghods, Reza Farzipoor Saen
Summary: The Covid-19 virus poses a global health threat, leading governments to take measures to control its spread. This study aims to enhance the efficiency of Covid-19 treatment centers by using Artificial Neural Network (ANN) to forecast their efficiency and provide benchmarks. The findings suggest that allocating more respiratory equipment, pulmonologists, and beds to treatment centers can reduce mortality rates and increase recovery rates.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Business
Majid Azadi, Saeed Yousefi, Reza Farzipoor Saen, Hadi Shabanpour, Fauzia Jabeen
Summary: The study proposes a network data envelopment analysis (NDEA) model and a deep learning approach for predicting the sustainability of healthcare supply chains (HSCs). Technological advances such as deep learning, artificial intelligence (AI), and Blockchain have gained importance in HSCs and are seen as competitive advantages. The use of advanced performance evaluation techniques, including DEA, has garnered considerable attention in enhancing HSCs' performance. The results highlight the top-ranking HSCs that utilize fewer facilities, have desirable outputs, and minimal undesirable outputs.
JOURNAL OF BUSINESS RESEARCH
(2023)
Article
Operations Research & Management Science
Majid Azadi, Mehdi Toloo, Fahimeh Ramezani, Reza Farzipoor Saen, Farookh Khadeer Hussain, Hajar Farnoudkia
Summary: The rapid growth of advanced technologies such as cloud computing in the Industry 4.0 era has brought numerous advantages. Evaluating the efficiency of cloud service providers (CSPs) is a challenge for customers. This study designs a decision support system that accurately evaluates the efficiency of multiple CSPs in a supply chain, taking into account undesirable outputs, integer-valued, and stochastic data.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Amirali Fathi, Reza Farzipoor Saen
Summary: This study focuses on the sustainability evaluation of transportation supply chains using data envelopment analysis (DEA) and Shannon's entropy technique. A common set of weights (CSW) model is developed to evaluate the sustainability of transportation supply chains. The proposed model is a two-stage network DEA model based on Shannon's entropy and can fully rank transport companies.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2023)
Article
Operations Research & Management Science
Seyed Amir Hossein Sadeghi, Reza Farzipoor Saen, Abbas Toloie Eshlaghy, Mahmoud Modiri
Summary: Evaluation of supply chain sustainability is a complex decision-making problem, and data envelopment analysis (DEA) is used to assess sustainability in supply chains. This research develops a network DEA (NDEA) model that considers fuzzy rough data to assess sustainability. The proposed model takes into account the internal interactions of decision-making units (DMUs) and assumes fuzzy inputs and outputs.
JOURNAL OF DECISION SYSTEMS
(2023)
Article
Operations Research & Management Science
Majid Azadi, T. C. E. Cheng, Reza Kazemi Matin, Reza Farzipoor Saen
Summary: This research develops a network data envelopment analysis model to assess the resilience and sustainability of healthcare supply chains (SCs) in response to the COVID-19 pandemic outbreak. The proposed model can handle different types of data and introduces a modified directional distance function for efficiency measurement. The performance of 28 healthcare SCs is evaluated to demonstrate the applicability and capability of the approach.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Elnaz Azadi, Zohreh Moghaddas, Reza Farzipoor Saen, Abbas Mardani, Majid Azadi
Summary: Supply chains are complex systems that involve interactions, components, and flows. The rise of green supply chains has prompted policymakers and managers to consider environmental factors alongside the economic aspect. However, current models struggle to evaluate the performance of green supply chains in an integrated manner. To address this issue, this paper proposes a network data envelopment analysis (NDEA) method as an effective approach for evaluating green supply chains.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Green & Sustainable Science & Technology
Majid Azadi, Hossein Azizi, Reza Farzipoor Saen
Summary: Coordination in providing sustainable and effective transport services is beneficial for both the public and private sectors. However, research on public-private coordination is rare and performance measurement of public-private transport is less explored. This paper contributes to the transportation field by developing a novel network data envelopment analysis (NDEA) model to measure the performance and coordination of public-private transport within multimodal transport networks. The model is based on the directional distance function (DDF) and provides insights into the sustainability and resource allocation among decision-making units (DMUs) in public-private transport networks.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Economics
Farhad Hosseinzadeh Lotfi, Reza Farzipoor Saen, Zohreh Moghaddas, Mohsen Vaez-Ghasemi
Summary: Desirable and undesirable outputs are produced together in most production activities, and they are interdependent. Reducing undesirable outputs may lead to a decrease in desirable ones as well. This study introduces and applies concepts and models to assess the sustainability of supply chains, considering the dependency between desirable and undesirable outputs in an SBM network system. A new network data envelopment analysis (NDEA) model based on the Slack Based Model (SBM) is developed, and a case study on wheat supply chains is presented to demonstrate various aspects of the proposed model, which considers both types of outputs.
SOCIO-ECONOMIC PLANNING SCIENCES
(2023)
Article
Computer Science, Interdisciplinary Applications
Xiaolin Wang, Liyi Zhan, Yong Zhang, Teng Fei, Ming-Lang Tseng
Summary: This study proposes an environmental cold chain logistics distribution center location model to reduce transportation costs and carbon emissions. It also introduces a hybrid arithmetic whale optimization algorithm to overcome the limitations of the conventional algorithm.
COMPUTERS & INDUSTRIAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Hong-yu Liu, Shou-feng Ji, Yuan-yuan Ji
Summary: This study proposes an architecture that utilizes Ethereum to investigate the production-inventory-delivery problem in Physical Internet (PI), and develops an iterative heuristic algorithm that outperforms other algorithms. However, due to gas prices and consumption, blockchain technology may not always be the optimal solution.
COMPUTERS & INDUSTRIAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Paraskevi Th. Zacharia, Elias K. Xidias, Andreas C. Nearchou
Summary: This article discusses the assembly line balancing problem in production lines with collaborative robots. Collaborative robots have the potential to improve automation, productivity, accuracy, and flexibility in manufacturing. The article explores the use of a problem-specific metaheuristic to solve this complex problem under uncertainty.
COMPUTERS & INDUSTRIAL ENGINEERING
(2024)
