Manufacturing Scheduling Systems, Jose M. Framinan; Rainer Leisten; Rub?n Ruiz Garc?

Автор: Palmer Richard, Palmer
Название: Maintenance Planning and Scheduling Handbook 3/E
ISBN: 007178411X ISBN-13(EAN): 9780071784115
Издательство: McGraw-Hill
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Цена: 89220.00 T
Наличие на складе: Невозможна поставка.
Описание: Fully updated and revised throughout, this is a new edition of the bestselling blockbuster that set the industry standard for maintenance planning.

Автор: Lihui Wang; Weiming Shen
Название: Process Planning and Scheduling for Distributed Manufacturing
ISBN: 184996646X ISBN-13(EAN): 9781849966467
Издательство: Springer
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Цена: 174130.00 T
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Описание: This is the first book to focus on emerging technologies for distributed intelligent decision-making in process planning and dynamic scheduling. The book provides a better understanding of the present state and future trends of research in this area.

Автор: Pinedo Michael L
Название: Scheduling
ISBN: 3319265784 ISBN-13(EAN): 9783319265780
Издательство: Springer
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Цена: 65210.00 T
Наличие на складе: Поставка под заказ.
Описание: This new edition provides an up-to-date coverage of important theoretical models in the scheduling literature as well as significant scheduling problems that occur in the real world.

Автор: Jacek Blazewicz; Klaus H. Ecker; Erwin Pesch; G?nt
Название: Handbook on Scheduling
ISBN: 3642429637 ISBN-13(EAN): 9783642429637
Издательство: Springer
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Цена: 181670.00 T
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Описание: This book explores scheduling problems in advanced planning and computer systems. The text examines a range of parameters: job priority, release times, due dates, processing times, resource usage and more, focusing on such aspects as computer systems and supply chain management.

Автор: Raymond Chiong; Sandeep Dhakal
Название: Natural Intelligence for Scheduling, Planning and Packing Problems
ISBN: 3642040381 ISBN-13(EAN): 9783642040382
Издательство: Springer
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Цена: 181670.00 T
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Описание: Natural intelligence based approaches for scheduling, planning and packing are discussed as a means to draw inspiration from nature. Evolutionary algorithms, ant colony optimisation and raindrop optimisation are among the solutions presented.

Автор: Raymond Chiong; Sandeep Dhakal
Название: Natural Intelligence for Scheduling, Planning and Packing Problems
ISBN: 3642260616 ISBN-13(EAN): 9783642260612
Издательство: Springer
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Цена: 181670.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Natural intelligence based approaches for scheduling, planning and packing are discussed as a means to draw inspiration from nature. Evolutionary algorithms, ant colony optimisation and raindrop optimisation are among the solutions presented.

Автор: Sarin
Название: Stochastic Scheduling
ISBN: 1107637902 ISBN-13(EAN): 9781107637900
Издательство: Cambridge Academ
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Цена: 70750.00 T
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Описание: In a stochastic environment, in which the processing time of a job is not known with certainty, a schedule is typically analyzed based on the expected value of a performance measure. This book presents algorithms to determine the variability of a schedule under various machine configurations and objective functions.

Автор: Wenkai Li; Yong Wu; Mark Goh
Название: Planning and Scheduling for Maritime Container Yards
ISBN: 3319170244 ISBN-13(EAN): 9783319170244
Издательство: Springer
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Цена: 104480.00 T
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Описание:

Introduction.- Maritime Terminal Operational Problems.- Discrete Time Model and Algorithms for Container Yard Crane Scheduling.- A Continuous Time Model for Multiple Yard Crane Scheduling with Last Minute Job Arrivals.- Heuristic Approach.- Validation via Simulation.

Автор: Khalid Karam Abd
Название: Intelligent Scheduling of Robotic Flexible Assembly Cells
ISBN: 3319262955 ISBN-13(EAN): 9783319262956
Издательство: Springer
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Цена: 113190.00 T
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Описание: Background and Research Scope.- Literature Review and Research Objectives.- Development of an Intelligent Methodology for Scheduling RFAC.- Case Study 1: Application of the Developed Methodology Using Fuzzy Logic and Simulation.- Simulation Modelling and Analysis of Dynamic Scheduling in RFAC.- Development of an Optimization Approach for Dynamic Scheduling Problems in RFAC.- Case Study 2: Application of Hybrid Fuzzy MCDM Approach to Optimize Dynamic Scheduling in RFAC.- Conclusions and Recommendations for Further Work.