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Edité par Taylor & Francis Ltd, London, 2025
ISBN 10 : 1032634391 ISBN 13 : 9781032634395
Langue: anglais
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Ajouter au panierPaperback. Etat : new. Paperback. This book introduces and analyses recent trends and studies of sustainable logistics systems using AI-based meta-heuristics approaches, including AI-based meta-heuristics applied to supply chain network models, integrated multi-criteria decision-making approaches for green supply chain management, uncertain supply chain models etc. It emphasizes both theory and practice, providing methodological and theoretical basis as well as case references for sustainable logistics systems using AI based meta-heuristics.Most of multi-national enterprises today face the challenge of sustainable development for their logistics systems trying to meet or exceed customer expectations. Sustainable development attracts both researchers and industrial practitioners who are focused on the design and implementation of logistics system. AI-based meta-heuristics approaches has emerged as a capable method for quickly providing optimal or near-optimal solutions for the problems that exact optimization cannot solve. Recent advances in various AI-based meta-heuristics approaches can resolve various and complex logistics and supply chain problem types. This book mainly encompasses the most popular and frequently employed AI-based meta-heuristics approaches such as genetic algorithm, variable neighborhood search, multi-objective heuristic search and the hybrid of these approaches.The chapters in this book were originally published in the International Journal of Management Science and Engineering Management. This book emphasizes both theory and practice, providing methodological and theoretical basis as case references for Sustainable Logistics Systems using AI based Meta Heuristics. It encompasses the most frequently employed AI-based meta-heuristics approaches. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Edité par Taylor & Francis Ltd, London, 2025
ISBN 10 : 1032634391 ISBN 13 : 9781032634395
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Ajouter au panierPaperback. Etat : new. Paperback. This book introduces and analyses recent trends and studies of sustainable logistics systems using AI-based meta-heuristics approaches, including AI-based meta-heuristics applied to supply chain network models, integrated multi-criteria decision-making approaches for green supply chain management, uncertain supply chain models etc. It emphasizes both theory and practice, providing methodological and theoretical basis as well as case references for sustainable logistics systems using AI based meta-heuristics.Most of multi-national enterprises today face the challenge of sustainable development for their logistics systems trying to meet or exceed customer expectations. Sustainable development attracts both researchers and industrial practitioners who are focused on the design and implementation of logistics system. AI-based meta-heuristics approaches has emerged as a capable method for quickly providing optimal or near-optimal solutions for the problems that exact optimization cannot solve. Recent advances in various AI-based meta-heuristics approaches can resolve various and complex logistics and supply chain problem types. This book mainly encompasses the most popular and frequently employed AI-based meta-heuristics approaches such as genetic algorithm, variable neighborhood search, multi-objective heuristic search and the hybrid of these approaches.The chapters in this book were originally published in the International Journal of Management Science and Engineering Management. This book emphasizes both theory and practice, providing methodological and theoretical basis as case references for Sustainable Logistics Systems using AI based Meta Heuristics. It encompasses the most frequently employed AI-based meta-heuristics approaches. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Ajouter au panierPaperback. Etat : Brand New. 186 pages. 11.68x8.25x11.69 inches. In Stock.
Edité par Taylor & Francis Ltd, London, 2025
ISBN 10 : 1032634391 ISBN 13 : 9781032634395
Langue: anglais
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Ajouter au panierPaperback. Etat : new. Paperback. This book introduces and analyses recent trends and studies of sustainable logistics systems using AI-based meta-heuristics approaches, including AI-based meta-heuristics applied to supply chain network models, integrated multi-criteria decision-making approaches for green supply chain management, uncertain supply chain models etc. It emphasizes both theory and practice, providing methodological and theoretical basis as well as case references for sustainable logistics systems using AI based meta-heuristics.Most of multi-national enterprises today face the challenge of sustainable development for their logistics systems trying to meet or exceed customer expectations. Sustainable development attracts both researchers and industrial practitioners who are focused on the design and implementation of logistics system. AI-based meta-heuristics approaches has emerged as a capable method for quickly providing optimal or near-optimal solutions for the problems that exact optimization cannot solve. Recent advances in various AI-based meta-heuristics approaches can resolve various and complex logistics and supply chain problem types. This book mainly encompasses the most popular and frequently employed AI-based meta-heuristics approaches such as genetic algorithm, variable neighborhood search, multi-objective heuristic search and the hybrid of these approaches.The chapters in this book were originally published in the International Journal of Management Science and Engineering Management. This book emphasizes both theory and practice, providing methodological and theoretical basis as case references for Sustainable Logistics Systems using AI based Meta Heuristics. It encompasses the most frequently employed AI-based meta-heuristics approaches. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Ajouter au panierEtat : New. Jiuping Xu is Associate Vice President of Sichuan University, P.R. China, and Editor-in-Chief of International Journal of Management Science and Engineering Management. His research interests include decision science, engineering management.
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Ajouter au panierTaschenbuch. Etat : Neu. Sustainable Logistics Systems Using AI-based Meta-Heuristics Approaches | Jiuping Xu (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2025 | Routledge | EAN 9781032634395 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
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Ajouter au panierTaschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book emphasizes both theory and practice, providing methodological and theoretical basis as case references for Sustainable Logistics Systems using AI based Meta Heuristics. It encompasses the most frequently employed AI-based meta-heuristics approaches.
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Edité par Taylor & Francis Ltd Dez 2023, 2023
ISBN 10 : 1032634383 ISBN 13 : 9781032634388
Langue: anglais
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Ajouter au panierBuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book introduces and analyses recent trends and studies of sustainable logistics systems using AI-based meta-heuristics approaches, including AI-based meta-heuristics applied to supply chain network models, integrated multi-criteria decision-making approaches for green supply chain management, uncertain supply chain models etc. It emphasizes both theory and practice, providing methodological and theoretical basis as well as case references for sustainable logistics systems using AI based meta-heuristics.Most of multi-national enterprises today face the challenge of sustainable development for their logistics systems trying to meet or exceed customer expectations. Sustainable development attracts both researchers and industrial practitioners who are focused on the design and implementation of logistics system. AI-based meta-heuristics approaches has emerged as a capable method for quickly providing optimal or near-optimal solutions for the problems that exact optimization cannot solve. Recent advances in various AI-based meta-heuristics approaches can resolve various and complex logistics and supply chain problem types. This book mainly encompasses the most popular and frequently employed AI-based meta-heuristics approaches such as genetic algorithm, variable neighborhood search, multi-objective heuristic search and the hybrid of these approaches.The chapters in this book were originally published in the International Journal of Management Science and Engineering Management. 174 pp. Englisch.
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Ajouter au panierBuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book introduces and analyses recent trends and studies of sustainable logistics systems using AI-based meta-heuristics approaches, including AI-based meta-heuristics applied to supply chain network models, integrated multi-criteria decision-making approaches for green supply chain management, uncertain supply chain models etc. It emphasizes both theory and practice, providing methodological and theoretical basis as well as case references for sustainable logistics systems using AI based meta-heuristics.Most of multi-national enterprises today face the challenge of sustainable development for their logistics systems trying to meet or exceed customer expectations. Sustainable development attracts both researchers and industrial practitioners who are focused on the design and implementation of logistics system. AI-based meta-heuristics approaches has emerged as a capable method for quickly providing optimal or near-optimal solutions for the problems that exact optimization cannot solve. Recent advances in various AI-based meta-heuristics approaches can resolve various and complex logistics and supply chain problem types. This book mainly encompasses the most popular and frequently employed AI-based meta-heuristics approaches such as genetic algorithm, variable neighborhood search, multi-objective heuristic search and the hybrid of these approaches.The chapters in this book were originally published in the International Journal of Management Science and Engineering Management.