Da: California Books, Miami, FL, U.S.A.
EUR 78,02
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Da: Majestic Books, Hounslow, Regno Unito
EUR 73,77
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Da: PBShop.store US, Wood Dale, IL, U.S.A.
EUR 83,73
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Aggiungi al carrelloPAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
EUR 79,62
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Aggiungi al carrelloPAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 84,93
Quantità: 3 disponibili
Aggiungi al carrelloCondizione: New.
Da: Revaluation Books, Exeter, Regno Unito
EUR 100,72
Quantità: 2 disponibili
Aggiungi al carrelloPaperback. Condizione: Brand New. 216 pages. 6.14x0.45x9.21 inches. In Stock.
Da: moluna, Greven, Germania
EUR 77,70
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Aggiungi al carrelloCondizione: New. Irfan Ali earned his B.Sc., M.Sc., M.Phil., and Ph.D. degrees from Aligarh Muslim University. He is currently a working faculty member with the Department of Statistics and Operations Research, Aligarh Muslim University. He received the .
Lingua: Inglese
Editore: Taylor & Francis Ltd Jun 2026, 2026
ISBN 10: 1032821205 ISBN 13: 9781032821207
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 105,25
Quantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuware - This book comprehensively discusses nature-inspired algorithms, deep learning methods, applications of mathematical programming and artificial intelligence techniques. It will further cover important topic such as linking green supply chain management practices with competitiveness, industry 4.0, and social responsibility.This book: - Addresses solving practical problems such as supply chain management, take-off, and healthcare analytics using intelligent computing - Presents a comparative analysis of machine learning algorithms for power consumption prediction - Discusses a machine learning-based multi-objective optimization technique for load balancing in an integrated fog cloud environment - Illustrates a data-driven optimization concept for modeling environmental and economic sustainability - Explains the use of heuristics and metaheuristics in supply chain networks and the use of fuzzy optimization in sustainable development goals The text is primarily written for graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, mathematics and statistics, computer science and engineering.
Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2026
ISBN 10: 1032821205 ISBN 13: 9781032821207
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Paperback. Condizione: new. Paperback. This book comprehensively discusses nature-inspired algorithms, deep learning methods, applications of mathematical programming and artificial intelligence techniques. It will further cover important topic such as linking green supply chain management practices with competitiveness, industry 4.0, and social responsibility.This book:Addresses solving practical problems such as supply chain management, take-off, and healthcare analytics using intelligent computingPresents a comparative analysis of machine learning algorithms for power consumption predictionDiscusses a machine learning-based multi-objective optimization technique for load balancing in an integrated fog cloud environmentIllustrates a data-driven optimization concept for modeling environmental and economic sustainabilityExplains the use of heuristics and metaheuristics in supply chain networks and the use of fuzzy optimization in sustainable development goalsThe text is primarily written for graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, mathematics and statistics, computer science and engineering. This book comprehensively discusses nature-inspired algorithms, deep learning methods, applications of mathematical programming and artificial intelligence techniques. It will further cover important topic such as linking green supply chain management practices with competitiveness, industry 4.0 and social responsibility. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2026
ISBN 10: 1032821205 ISBN 13: 9781032821207
Da: CitiRetail, Stevenage, Regno Unito
EUR 44,17
Quantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: new. Paperback. This book comprehensively discusses nature-inspired algorithms, deep learning methods, applications of mathematical programming and artificial intelligence techniques. It will further cover important topic such as linking green supply chain management practices with competitiveness, industry 4.0, and social responsibility.This book:Addresses solving practical problems such as supply chain management, take-off, and healthcare analytics using intelligent computingPresents a comparative analysis of machine learning algorithms for power consumption predictionDiscusses a machine learning-based multi-objective optimization technique for load balancing in an integrated fog cloud environmentIllustrates a data-driven optimization concept for modeling environmental and economic sustainabilityExplains the use of heuristics and metaheuristics in supply chain networks and the use of fuzzy optimization in sustainable development goalsThe text is primarily written for graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, mathematics and statistics, computer science and engineering. This book comprehensively discusses nature-inspired algorithms, deep learning methods, applications of mathematical programming and artificial intelligence techniques. It will further cover important topic such as linking green supply chain management practices with competitiveness, industry 4.0 and social responsibility. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 91,29
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2026
ISBN 10: 1032821205 ISBN 13: 9781032821207
Da: AussieBookSeller, Truganina, VIC, Australia
EUR 76,96
Quantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: new. Paperback. This book comprehensively discusses nature-inspired algorithms, deep learning methods, applications of mathematical programming and artificial intelligence techniques. It will further cover important topic such as linking green supply chain management practices with competitiveness, industry 4.0, and social responsibility.This book:Addresses solving practical problems such as supply chain management, take-off, and healthcare analytics using intelligent computingPresents a comparative analysis of machine learning algorithms for power consumption predictionDiscusses a machine learning-based multi-objective optimization technique for load balancing in an integrated fog cloud environmentIllustrates a data-driven optimization concept for modeling environmental and economic sustainabilityExplains the use of heuristics and metaheuristics in supply chain networks and the use of fuzzy optimization in sustainable development goalsThe text is primarily written for graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, mathematics and statistics, computer science and engineering. This book comprehensively discusses nature-inspired algorithms, deep learning methods, applications of mathematical programming and artificial intelligence techniques. It will further cover important topic such as linking green supply chain management practices with competitiveness, industry 4.0 and social responsibility. 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.