Article
Mathematics
Mehdi Keshavarz-Ghorabaee
Summary: The sustainable Supplier Evaluation and Selection and Order Allocation (SSOA) problem is important in supply chain management to improve performance, reduce costs, and enhance customer satisfaction. To address this problem, an integrated methodology is proposed that combines different techniques, such as the Radius of Gyration (ROG) ranking method for interval type-2 fuzzy sets and the Simple Multi-Attribute Rating Technique (SMART) for subjective weights. The methodology also utilizes a Weighted Aggregated Sum Product Assessment (WASPAS) method and a multi-objective decision-making (MODM) model for supplier evaluation and order allocation. This methodology offers a comprehensive approach to handling uncertainties and promoting sustainability in supply chain management.
Article
Computer Science, Interdisciplinary Applications
Liguo Fei, Yuqiang Feng, Hongli Wang
Summary: The paper introduces a novel human-centric heterogeneous multi-attribute decision-making approach based on Dempster-Shafer theory, which can better adapt to the diverse backgrounds and preferences of decision-makers. The approach is built on subjective attitudes of decision-makers, incorporating human cognitive aspects.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Environmental Sciences
Fatemeh Alamroshan, Mahyar La'li, Mohsen Yahyaei
Summary: The research addresses the supplier selection problem in the supply chain management area, focusing on green and agile aspects. A hybrid fuzzy decision-making approach is developed using FDEMATEL, FBWM, FANP, and FVIKOR methods, with a case study in the medical devices industry. The study finds that price and greenness are crucial factors in supplier selection, along with material costs, environmental performance evaluation, manufacture flexibility, service level, and system reliability.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Environmental Sciences
Alireza Fallahpour, Sina Nayeri, Mohammad Sheikhalishahi, Kuan Yew Wong, Guangdong Tian, Amir Mohammad Fathollahi-Fard
Summary: This study introduces a fuzzy decision framework to investigate the sustainable-resilient supplier selection problem in the palm oil industry in Malaysia. A hyper-hybrid model is developed using FDEMATEL, FBWM, FANP, and FIS methods. The findings of the study indicate high performance of the proposed framework in identifying important criteria for supplier selection.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Hesam Shidpour, Mohsen Shidpour, Erfan Babaee Tirkolaee
Summary: This study presents a multi-phase methodology to address the challenges of integrating Corporate Social Responsibility (CSR) in Supplier Selection and Order Allocation Problem (SSOAP) in developing countries. A multi-objective model is developed based on traditional criteria and takes into account the concerns of senior managers. The study also introduces new methods for evaluating suppliers' CSR practices and ranking solutions.
APPLIED SOFT COMPUTING
(2023)
Article
Operations Research & Management Science
Dawoon Jung, Bosung Kim, Seung Ho Yoo
Summary: In response to dynamic market conditions, manufacturers are increasingly focusing on inducing collaboration between suppliers to share problem-solving ideas, technical advice, and managerial knowledge. However, supplier-supplier collaboration can be challenging if the suppliers compete for the same order. This study explores how a manufacturer can leverage order allocation policies to facilitate collaboration between competing suppliers.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Environmental Sciences
Qiushuang Wei, Chao Zhou
Summary: This paper provides insights into electric vehicle supplier selection from the perspective of government agencies and public bodies using an integrated multi-criteria decision-making framework. Through a case study and analysis, it determines the importance of criteria such as bad environmental record, cost, quality, service, and environmental initiatives in electric vehicle supplier selection.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Hassan Ali, Jingwen Zhang
Summary: The selection of potential suppliers in the manufacturing industries has become a major challenge due to the spread of covid-19 and natural calamities. This study proposes a holistic model that combines economic, environmental, and transportation risk factors for global green supplier selection and order allocation in the textile industry. The proposed methodology effectively manages data uncertainties and can assist in overcoming current shortcomings and developing long-term relationships with buyers.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Interdisciplinary Applications
Sadeque Hamdan, Ali Cheaitou, Amir Shikhli, Imad Alsyouf
Summary: We study a multi-period single-product green supplier selection and order allocation problem where suppliers' availability, cost, and green performance vary over time. Different discount schemes are considered, and a bi-objective linear programming model is formulated to maximize the green value and minimize the total cost. Numerical analysis shows the effectiveness of a heuristic approach and the advantage of an all-unit discount scheme in balancing green value and cost.
COMPUTERS & OPERATIONS RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Zahra Sadat Hosseini, Simme Douwe Flapper, Mohammadali Pirayesh
Summary: This paper addresses the issue of sustainable supplier selection in supply chain management. It proposes a hybrid method for evaluating and ranking suppliers, and presents a bi-objective mathematical model to balance sustainability and economic cost. The proposed approach is compared with existing methods and sensitivity analysis is conducted to assess its effectiveness and advantages.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Green & Sustainable Science & Technology
Valentina Di Pasquale, Raffaele Iannone, Maria Elena Nenni, Stefano Riemma
Summary: Existing models for order allocation mainly consider environmental attributes and neglect economic and social attributes. Therefore, this paper proposes a model for green order allocation in a high operational variability supply chain, which considers uncertainty, limited capacity, minimum levels, and scores of suppliers, as well as emissions related to production, ordering, maintenance, and transport. The validation of the model shows that it achieves lower costs and TBL impacts compared to models that only consider TBL scores in supplier selection, thus helping firms increase sustainability throughout the supply chain.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Computer Science, Artificial Intelligence
Liangcheng Xu, Xiaojian Hu, Yue Zhang, Jingsheng Feng, Suizhi Luo
Summary: In this paper, a multiobjective team optimization model is proposed to tackle the issues of information vagueness and uncertainty in order demand, logistics service provider (LSP) service capacity, and target preference in emergency events in the customized logistics service supply chain. Fuzzy objective coefficients, fuzzy constraint parameters, and a fuzzy single objective weighting technique are introduced to reflect the decision-maker preferences and satisfaction level. Sensitivity analysis is conducted to explore the effects of fuzzy coefficients and parameters on the decision-making process.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Thermodynamics
M. Alipour, R. Hafezi, Pratibha Rani, Mehdi Hafezi, Abbas Mardani
Summary: This paper presents an integrated approach using entropy, SWARA, and COPRAS methods for FCH supplier selection, overcoming the shortcomings of traditional methods by combining objective and subjective weights, and using Pythagorean fuzzy set to handle uncertain information.
Article
Computer Science, Interdisciplinary Applications
Tai-Wu Chang, Chun-Jui Pai, Huai-Wei Lo, Shu-Kung Hu
Summary: This paper proposes a sustainable supplier evaluation and selection framework for electronics manufacturing, including four dimensions of economic, social, environmental, and institutional sustainability. By integrating a modified method that combines attribute ratio analysis and the preference ranking organization method, an improved hybrid decision-making analysis model is developed.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Interdisciplinary Applications
Chunguang Bai, Qingyun Zhu, Joseph Sarkis
Summary: Supplier selection and order allocation (SSOA) is an emerging and important issue in supply chain management. This paper introduces a foundational multi-objective mathematical model to bridge this research gap. Findings provide theoretical and managerial insights and future research guidance on carbon neutrality and net-zero implications for SSOA.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Computer Science, Software Engineering
S. Asadi, N. Mahdavi-Amiri, Zs Darvay, P. R. Rigo
Summary: In this study, a feasible interior-point algorithm is proposed to solve the horizontal linear complementarity problem defined on a Cartesian product of symmetric cones. The algorithm does not rely on a usual barrier function but utilizes the Nesterov-Todd scaling point to scale the full steps. The method generates search directions leading to the full-NT steps by algebraically transforming the centring equation of the system using the induced barrier of a positive-asymptotic kernel function. The global convergence and local quadratic rate of convergence of the proposed method are established.
OPTIMIZATION METHODS & SOFTWARE
(2022)
Article
Computer Science, Interdisciplinary Applications
Navid Gholamian, Iraj Mahdavi, Nezam Mahdavi-Amiri, Reza Tavakkoli-Moghaddam
Summary: This article discusses a complex supply chain model aimed at improving sustainability and reducing costs. It considers multiple objective functions and decision levels, proposing a fuzzy approach to address uncertainties.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Software Engineering
Hani Ahmadzadeh, Nezam Mahdavi-Amiri
Summary: The algorithm proposed in this study utilizes inexact solutions of QPs to ensure global convergence, guaranteeing descent direction in feasible and infeasible iterations. Additionally, the introduction of a nonmonotone filter strategy enhances the robustness and efficiency of the algorithm.
OPTIMIZATION METHODS & SOFTWARE
(2022)
Article
Engineering, Biomedical
Nooshin Moradi, Nezam Mandavi-Amiri
Summary: This paper proposes a method for multi-class segmentation of dermoscopic images based on joint dictionary learning, achieving better results, especially for challenging skin lesions. The experimental results demonstrate the efficiency and effectiveness of the proposed method in producing reliable results for clinical applications, even using limited training data.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2021)
Article
Operations Research & Management Science
Saeed Khanchehzarrin, Maral Shahmizad, Iraj Mahdavi, Nezam Mahdavi-Amiri, Peiman Ghasemi
Summary: A new mixed-integer nonlinear programming model is proposed for the time-dependent vehicle routing problem, using a tabu search optimization algorithm to solve large problems and evaluating the effectiveness of the algorithm through modeling and calculations.
RAIRO-OPERATIONS RESEARCH
(2021)
Article
Robotics
Hamed Fazlollahtabar
Summary: Industry 4.0 integrated with robotic and digital fabrication technologies has attracted the attention of manufacturing researchers. This paper proposes an intelligent control system based on SCADA in the IoT platform for processing configuration and reconfiguration of an autonomous assembly system, and the implementation study confirms its effectiveness.
Article
Statistics & Probability
Ali Sadeghi, Mansour Saraj, Nezam Mahdavi Amiri
Summary: This paper utilizes interior-point methods for solving fractional programming problems with second order cone constraints, proposing a logarithmic barrier function to demonstrate self-concordance and presenting an algorithm for computing ε-solutions. A numerical example is provided to illustrate the approach.
PAKISTAN JOURNAL OF STATISTICS AND OPERATION RESEARCH
(2021)
Article
Engineering, Industrial
Samane Babaeimorad, Parviz Fattahi, Hamed Fazlollahtabar
Summary: The paper presents an integrated strategy for inventory control and preventive maintenance planning for a single-machine production system. By using a numerical algorithm to find the optimal policy, it reduces production system costs and effectively deals with customer loss.
JOURNAL OF QUALITY IN MAINTENANCE ENGINEERING
(2022)
Article
Economics
Saeed Khanchehzarrin, Mona Ghaebi Panah, Nezam Mahdavi-Amiri, Saber Shiripour
Summary: In recent years, the frequency and severity of natural disasters worldwide have increased, causing significant financial and human losses. Decision-makers are therefore seeking ways to provide relief and reduce these losses. This study proposes a multi-objective bi-level model for the disaster location-routing problem, which considers multiple suppliers and supply risk. The findings highlight the importance of public donations in providing low-risk, high-priority goods to improve relief efforts.
SOCIO-ECONOMIC PLANNING SCIENCES
(2022)
Article
Operations Research & Management Science
Ja'far Dehghanpour, Nezam Mahdavi-Amiri
Summary: This article proposes an approach to convert the orthogonal nonnegative matrix factorization problem into a non-convex constraint problem and applies a penalty function to handle the non-convex constraints. The method performs well in partitioning clustering problems.
ANNALS OF OPERATIONS RESEARCH
(2022)
Article
Computer Science, Theory & Methods
Elham Monifi, Nezam Mahdavi-Amiri
Summary: This study proposes a time-varying dual accelerated gradient method for minimizing the average of multiple strongly convex and smooth functions over a time-varying network. Experimental results demonstrate its high efficiency.
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
(2022)
Article
Green & Sustainable Science & Technology
Zahra Taherikhonakdar, Hamed Fazlollahtabar
Summary: These days software plays an important role in various aspects of our lives. With the increasing use of computers, mobile applications, and embedded systems, the energy consumption of software has become a growing concern. Green IT has emerged as a focus on optimizing software solutions to reduce energy consumption. Despite the importance of green software development, few developers pay attention to software energy consumption, and even fewer users care about the energy consumption of the software they use. This article aims to help software developers develop energy-efficient software and inform users about the energy consumption of the software they use in order to ultimately reduce the negative impact of software on the environment.
ENVIRONMENTAL PROGRESS & SUSTAINABLE ENERGY
(2023)
Article
Computer Science, Software Engineering
Hamed Fazlollahtabar
Summary: Supplier selection is a significant problem in supply chain management, involving concurrent decision-making on key performance indicators based on multi-dimensional data. Recent studies have examined the supplier selection problem in various applied cases, with a focus on a range of criteria. This problem becomes more pronounced in industries with high levels of investment, such as the renewable energy sector. This article presents a new method that encompasses all relevant indices for effective supplier selection. The proposed algorithm utilizes decision tree (DT) indices to group criteria and sub-criteria, and uses a machine learning (RML) approach to handle uncertain data through rough comparisons and weighing. The method also includes a transformation (T) step to obtain crisp values and a ranking (R) of suppliers. A case study on renewable energy supplier selection demonstrates the effectiveness of the proposed method, particularly in handling big data through machine learning techniques. The article also discusses the managerial implications of this method as decision support.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2023)
Article
Business
Nasim Ganjavi, Hamed Fazlollahtabar
Summary: In today's competitive environment, quality management is crucial for companies to reach a larger market share and economic success. The integration of physical machinery systems with digital networking in Industry 4.0 provides extensive opportunities for quality-related issues. To encompass all dimensions effective on quality management, it is necessary to process a large amount of data within the context of Industry 4.0. Advanced production systems and quality management are complementary resources to enhance functionality and gain a higher competitive advantage.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2023)
Article
Operations Research & Management Science
Reza Ghanbari, Khatere Ghorbani-Moghadam, Nezam Mahdavi-Amiri
Summary: The study introduces a modified Kerre's method for comparing LR fuzzy numbers and applies it to solving fuzzy linear programming problems with LR coefficients. By presenting a TV-MOPSO algorithm for computing the Pareto front, the effectiveness of the proposed algorithm is demonstrated through illustrative examples with triangular fuzzy coefficients.
