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Record Nr. |
UNINA9910254284503321 |
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Autore |
Liu Xinbao |
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Titolo |
Optimization and Management in Manufacturing Engineering : Resource Collaborative Optimization and Management through the Internet of Things / / by Xinbao Liu, Jun Pei, Lin Liu, Hao Cheng, Mi Zhou, Panos M. Pardalos |
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Pubbl/distr/stampa |
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Cham : , : Springer, , [2017] |
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©2017 |
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ISBN |
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Descrizione fisica |
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1 online resource (xviii, 264 pages) : illustrations |
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Collana |
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Springer optimization and its applications, , 1931-6828 ; ; volume 126 |
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Disciplina |
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Soggetti |
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Operations research |
Management science |
Business logistics |
Mathematical models |
Algorithms |
Operations Research, Management Science |
Supply Chain Management |
Mathematical Modeling and Industrial Mathematics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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1. Information Sharing and Risk Management -- 2. Optimal Allocation of Decision-Making Authority in IoT-based Manufacturing Enterprises -- 3. Dynamic Coordinated Supply Chain Scheduling in an IoT Environment -- 4. Hybrid Manufacturing Distributed Inventory Management with Sharing Logistics -- 5. Cutting stock problem with the IoT -- 6. Total Quality Management of the Product Life Cycle in an IoT Environment -- 7. Life Cycle Assessment in an IoT Environment. –References. |
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Sommario/riassunto |
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Problems facing manufacturing clusters that intersect information technology, process management, and optimization within the Internet of Things (IoT) are examined in this book. Recent advances in information technology have transformed the use of resources and data |
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exchange, often leading to management and optimization problems attributable to technology limitations and strong market competition. This book discusses several problems and concepts which makes significant connections in the areas of information sharing, organization management, resource operations, and performance assessment. Geared toward practitioners and researchers, this treatment deepens the understanding between resource collaborative management and advanced information technology. Those in manufacturing will utilize the numerous mathematical models and methods offered to solve practical problems related to cutting stock, supply chain scheduling, and inventory management. Academics and students with a basic knowledge of manufacturing, combinatorics, and linear programming will find that this discussion widens the research area of resource collaborative management and unites the fields of information technology, manufacturing management, and optimization. . |
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