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Synopsis
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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
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, and management science.
Mitsuo Gen is Senior Research Scientist of Fuzzy Logic Systems Institute and Visiting Professor at Tokyo University of Science, Japan. His research interests include soft computing, evolutionary algorithms, intelligent manufacturing, and sustainable closed supply chain.
Zongmin Li is Professor of Business School, Sichuan University, P. R. China, and Managing Editor of International Journal of Management Science and Engineering Management. Her research interests include data-driven decision making and big data analytics.
YoungSu Yun is Professor of Division of Business Administration at Chosun University, South Korea. His research interests include sustainable closed supply chain system, engineering optimization design and evolutionary algorithms.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Sustainable Logistics Systems Using AI-based Meta-Heuristics Approaches
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Sustainable Logistics Systems Using AI-based Meta-Heuristics Approaches (Paperback)
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ISBN 10 : 1032634391
ISBN 13 : 9781032634395
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Paperback. 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. N° de réf. du vendeur 9781032634395
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Sustainable Logistics Systems Using AI-based Meta-Heuristics Approaches (Paperback)
Edité par
Taylor & Francis Ltd, London, 2025
ISBN 10 : 1032634391
ISBN 13 : 9781032634395
Neuf
Paperback
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Paperback. 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. N° de réf. du vendeur 9781032634395
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Sustainable Logistics Systems Using AI-based Meta-Heuristics Approaches (Paperback)
Edité par
Taylor & Francis Ltd, London, 2025
ISBN 10 : 1032634391
ISBN 13 : 9781032634395
Neuf
Paperback
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Paperback. 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. N° de réf. du vendeur 9781032634395
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Taschenbuch. 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. N° de réf. du vendeur 9781032634395
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