This book looks at how to combine metaheuristic optimization algorithms and fuzzy decision-making methods to improve the sustainability and effectiveness of supply chains. Mathematical and metaheuristic optimization methods based on natural processes, combined with fuzzy decision-making, enable the construction of models that can effectively address the multifaceted issues of contemporary supply chains. This book offers a variety of decision-making techniques, including entropy measures, distance measures, coefficient correlation, aggregating operators, TOPSIS, EDAS, and more. This book overcomes the drawbacks of existing fuzzy decision-making methods. The book also presents case studies that demonstrate the application of metaheuristic decision-making algorithms to improve the sustainability and viability of supply chains. One such notable example is green supplier selection in supply chain management. The changing supply chain management landscape offers many areas for future research, like investigating the intersection of mathematical and metaheuristic fuzzy decision-making algorithms with new technologies such as the Internet of Things (IoT) and artificial intelligence, which can create more responsive and adaptive supply chains.
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Dr. Kamal Kumar is listed in the top 2% of cited scientists list of Stanford University and Elsevier B.V. He is an assistant professor at Amity University Haryana, Gurugram, India. Dr. Kumar received his doctoral degree at Thapar Institute of Engineering & Technology Patiala, Punjab, India, in 2020. He has more than 9 years of teaching experience in different subjects of engineering mathematics, and statistics. His current research interest is in fuzzy decision making, aggregation operators, soft computing, and uncertainty theory. He has published more than 55 international articles in different reputed SCI journals. He has published an edited book in CRC Press. He has also published 5 book chapters and 3 patents. His Google citation is over 2500 with h-index 23 and i10 index 30. He is an associate editor in the journal “PLOS one”, “Journal of Applied Mathematics” and “ international journal of mathematical engineering and management sciences ”.
Dr Shahid Ahmad Bhat is a Postdoctoral Researcher at LUT Business School, LUT University, Finland, focusing on research and teaching. He earned his Ph.D. in Applied Mathematics (Operations Research) from Thapar Institute of Engineering and Technology (TIET), Punjab, India, in collaboration with the Indian Institute of Technology (IIT) Roorkee. His research specializes in developing advanced Multi-Attribute Decision-Making (MADM) methods in fuzzy environments. Previously, he worked as a Postdoctoral Fellow at the United Arab Emirates University, contributing to sustainable and resilient global supply chain models during the COVID-19 pandemic. His research interests include supply chain sustainability using AI, optimization techniques, fuzzy mathematical modelling, and MCMD. He has published in leading journals like Engineering Applications of Artificial Intelligence and Applied Soft Computing, Expert Systems with Applications, Resources Policy, Knowledge-based system, IEEE Access etc with h-index: 11.
Dr. Paul Augustine Ejegwa is an experienced teacher and researcher in mathematics with specialization in fuzzy mathematics, decision making, and computational intelligence. He is an Assistance Professor in mathematics at the Joseph Sarwuan Tarka University (Makurdi, Nigeria) and has published over 100 articles, book chapters and conference proceedings indexed in ISI and Scopus. He is is listed in the top 2% cited scientists list of Stanford University and Elsevier B.V. Dr. Ejegwa is an editorial member and reviewer for several reputable journals like Heliyon, Mathematics, AIMS Mathematics, etc. He is a member of the Asian Council of Science Editors, The International Society of Fuzzy Sets Extensions and Applications, Teachers’ Registration Council of Nigeria, Nigerian Mathematical Society, and MathTech Thinking Foundation.
Dr. Reeta Bhardwaj is an Assistant Professor in the Department of Mathematics at the Amity School of Applied Sciences, Amity University Haryana, India.With a Ph.D. in Mathematics, specializing in Stochastic and Fuzzy Modelling from Amity University Haryana, she has developed expertise in decision-making algorithms and techniques using fuzzy sets and logic. With over 18 years of experience in teaching and research, she has significantly contributed to the academic community. She has published more than 50 research articles/book chapters/conference proceedings in prestigious SCOPUS/SCI journals, she has made significant contributions to the field of mathematics, particularly in the areas of queuing theory, fuzzy decision making and stochastic modeling. In addition to research, she actively contributes to the academic community by reviewing articles for reputed journals.
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Hardcover. Condizione: new. Hardcover. This book looks at how to combine metaheuristic optimization algorithms and fuzzy decision-making methods to improve the sustainability and effectiveness of supply chains. Mathematical and metaheuristic optimization methods based on natural processes, combined with fuzzy decision-making, enable the construction of models that can effectively address the multifaceted issues of contemporary supply chains. This book offers a variety of decision-making techniques, including entropy measures, distance measures, coefficient correlation, aggregating operators, TOPSIS, EDAS, and more. This book overcomes the drawbacks of existing fuzzy decision-making methods. The book also presents case studies that demonstrate the application of metaheuristic decision-making algorithms to improve the sustainability and viability of supply chains. One such notable example is green supplier selection in supply chain management. The changing supply chain management landscape offers many areas for future research, like investigating the intersection of mathematical and metaheuristic fuzzy decision-making algorithms with new technologies such as the Internet of Things (IoT) and artificial intelligence, which can create more responsive and adaptive supply chains. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Codice articolo 9783119142663
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Condizione: New. Dr. Kamal Kumar is listed in the top 2% of cited scientists list of Stanford University and Elsevier B.V. He is an assistant professor at Amity University Haryana, Gurugram, India. Dr. Kumar received his doctoral degree at Thapar Institu. Codice articolo 2860126258
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Hardcover. Condizione: new. Hardcover. This book looks at how to combine metaheuristic optimization algorithms and fuzzy decision-making methods to improve the sustainability and effectiveness of supply chains. Mathematical and metaheuristic optimization methods based on natural processes, combined with fuzzy decision-making, enable the construction of models that can effectively address the multifaceted issues of contemporary supply chains. This book offers a variety of decision-making techniques, including entropy measures, distance measures, coefficient correlation, aggregating operators, TOPSIS, EDAS, and more. This book overcomes the drawbacks of existing fuzzy decision-making methods. The book also presents case studies that demonstrate the application of metaheuristic decision-making algorithms to improve the sustainability and viability of supply chains. One such notable example is green supplier selection in supply chain management. The changing supply chain management landscape offers many areas for future research, like investigating the intersection of mathematical and metaheuristic fuzzy decision-making algorithms with new technologies such as the Internet of Things (IoT) and artificial intelligence, which can create more responsive and adaptive supply chains. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9783119142663
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Buch. Condizione: Neu. Neuware - This book looks at how to combine metaheuristic optimization algorithms and fuzzy decision-making methods to improve the sustainability and effectiveness of supply chains. Mathematical and metaheuristic optimization methods based on natural processes, combined with fuzzy decision-making, enable the construction of models that can effectively address the multifaceted issues of contemporary supply chains. This book offers a variety of decision-making techniques, including entropy measures, distance measures, coefficient correlation, aggregating operators, TOPSIS, EDAS, and more. This book overcomes the drawbacks of existing fuzzy decision-making methods. The book also presents case studies that demonstrate the application of metaheuristic decision-making algorithms to improve the sustainability and viability of supply chains. One such notable example is green supplier selection in supply chain management. The changing supply chain management landscape offers many areas for future research, like investigating the intersection of mathematical and metaheuristic fuzzy decision-making algorithms with new technologies such as the Internet of Things (IoT) and artificial intelligence, which can create more responsive and adaptive supply chains. Codice articolo 9783119142663
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Buch. Condizione: Neu. Fuzzy Decision-Making Algorithms | Mathematical Optimization, Metaheuristic Optimization, Supply Chain Management | Kamal Kumar (u. a.) | Buch | X | Englisch | 2026 | De Gruyter | EAN 9783119142663 | Verantwortliche Person für die EU: Walter de Gruyter GmbH, De Gruyter GmbH, Genthiner Str. 13, 10785 Berlin, productsafety[at]degruyterbrill[dot]com | Anbieter: preigu. Codice articolo 135632498
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