Coverart for item
The Resource Configurable intelligent optimization algorithm : design and practice in manufacturing, Fei Tao, Lin Zhang, Yuanjun Laili, (electronic book)

Configurable intelligent optimization algorithm : design and practice in manufacturing, Fei Tao, Lin Zhang, Yuanjun Laili, (electronic book)

Label
Configurable intelligent optimization algorithm : design and practice in manufacturing
Title
Configurable intelligent optimization algorithm
Title remainder
design and practice in manufacturing
Statement of responsibility
Fei Tao, Lin Zhang, Yuanjun Laili
Creator
Contributor
Author
Subject
Language
eng
Summary
Presenting the concept and design and implementation of configurable intelligent optimization algorithms in manufacturing systems, this book provides a new configuration method to optimize manufacturing processes. It provides a comprehensive elaboration of basic intelligent optimization algorithms, and demonstrates how their improvement, hybridization and parallelization can be applied to manufacturing. Furthermore, various applications of these intelligent optimization algorithms are exemplified in detail, chapter by chapter. The intelligent optimization algorithm is not just a single algorit
Member of
Cataloging source
GW5XE
http://library.link/vocab/creatorName
Tao, Fei
Dewey number
519.6
Illustrations
illustrations
Index
no index present
LC call number
QA402.5
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
http://library.link/vocab/relatedWorkOrContributorName
  • Zhang, Lin
  • Laili, Yuanjun
Series statement
Springer Series in Advanced Manufacturing,
http://library.link/vocab/subjectName
Mathematical optimization
Label
Configurable intelligent optimization algorithm : design and practice in manufacturing, Fei Tao, Lin Zhang, Yuanjun Laili, (electronic book)
Instantiates
Publication
Copyright
Antecedent source
unknown
Bibliography note
Includes bibliographical references
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • Acknowledgements; Contents; Part IIntroduction and Overview; 1 Brief History and Overview of Intelligent Optimization Algorithms; 1.1...Introduction; 1.2...Brief History of Intelligent Optimization Algorithms; 1.3...Classification of Intelligent Algorithms; 1.4...Brief Review of Typical Intelligent Optimization Algorithms; 1.4.1 Review of Evolutionary Learning Algorithms; 1.4.1.1 Genetic Algorithm; 1.4.1.2 Immune Algorithm; 1.4.2 Review of Neighborhood Search Algorithms; 1.4.2.1 Simulated Annealing Algorithm; 1.4.2.2 Iterative Local Search; 1.4.3 Review of Swarm Intelligence Algorithm
  • 1.4.3.1 Ant Colony Optimization1.4.3.2 Particle Swarm Optimization; 1.5...The Classification of Current Studies on Intelligent Optimization Algorithm; 1.5.1 Algorithm Innovation; 1.5.2 Algorithm Improvement; 1.5.3 Algorithm Hybridization; 1.5.4 Algorithm Parallelization; 1.5.5 Algorithm Application; 1.6...Development Trends; 1.6.1 Intellectualization; 1.6.2 Service-Orientation; 1.6.3 Application-Oriented; 1.6.4 User-Centric; 1.7...Summary; References; 2 Recent Advances of Intelligent Optimization Algorithm in Manufacturing; 2.1...Introduction
  • 2.2...Classification of Optimization Problems in Manufacturing2.2.1 Numerical Function Optimization; 2.2.2 Parameter Optimization; 2.2.3 Detection and Classification; 2.2.4 Combinatorial Scheduling; 2.2.5 Multi-disciplinary Optimization; 2.2.6 Summary of the Five Types of Optimization Problems in Manufacturing; 2.3...Challenges for Addressing Optimization Problems in Manufacturing; 2.3.1 Balance of Multi-objectives; 2.3.2 Handling of Multi-constraints; 2.3.3 Extraction of Priori Knowledge; 2.3.4 Modeling of Uncertainty and Dynamics; 2.3.5 Transformation of Qualitative and Quantitative Features
  • 2.3.6 Simplification of Large-Scale Solution Space2.3.7 Jumping Out of Local Convergence; 2.4...An Overview of Optimization Methods in Manufacturing; 2.4.1 Empirical-Based Method; 2.4.2 Prediction-Based Method; 2.4.3 Simulation-Based Method; 2.4.4 Model-Based Method; 2.4.5 Tool-Based Method; 2.4.6 Advanced-Computing-Technology-Based Method; 2.4.7 Summary of Studies on Solving Methods; 2.5...Intelligent Optimization Algorithms for Optimization Problems in Manufacturing; 2.6...Challenges of Applying Intelligent Optimization Algorithms in Manufacturing; 2.6.1 Problem Modeling
  • 2.6.2 Algorithm Selection2.6.3 Encoding Scheming; 2.6.4 Operator Designing; 2.7...Future Approaches for Manufacturing Optimization; 2.8...Future Requirements and Trends of Intelligent Optimization Algorithm in Manufacturing; 2.8.1 Integration; 2.8.2 Configuration; 2.8.3 Parallelization; 2.8.4 Executing as Service; 2.9...Summary; References; Part IIDesign and Implementation; 3 Dynamic Configuration of Intelligent Optimization Algorithms; 3.1...Concept and Mainframe of DC-IOA; 3.1.1 Mainframe of DC-IOA; 3.1.2 Problem Specification and Construction of Algorithm Library in DC-IOA; 3.2...Case Study
Control code
SPR889942592
Dimensions
unknown
Extent
1 online resource (xiii, 361 pages)
File format
unknown
Form of item
online
Isbn
9783319088402
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other control number
10.1007/978-3-319-08840-2
Other physical details
illustrations (some color).
Quality assurance targets
not applicable
Reformatting quality
unknown
Reproduction note
Electronic resource.
Sound
unknown sound
Specific material designation
remote
Label
Configurable intelligent optimization algorithm : design and practice in manufacturing, Fei Tao, Lin Zhang, Yuanjun Laili, (electronic book)
Publication
Copyright
Antecedent source
unknown
Bibliography note
Includes bibliographical references
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • Acknowledgements; Contents; Part IIntroduction and Overview; 1 Brief History and Overview of Intelligent Optimization Algorithms; 1.1...Introduction; 1.2...Brief History of Intelligent Optimization Algorithms; 1.3...Classification of Intelligent Algorithms; 1.4...Brief Review of Typical Intelligent Optimization Algorithms; 1.4.1 Review of Evolutionary Learning Algorithms; 1.4.1.1 Genetic Algorithm; 1.4.1.2 Immune Algorithm; 1.4.2 Review of Neighborhood Search Algorithms; 1.4.2.1 Simulated Annealing Algorithm; 1.4.2.2 Iterative Local Search; 1.4.3 Review of Swarm Intelligence Algorithm
  • 1.4.3.1 Ant Colony Optimization1.4.3.2 Particle Swarm Optimization; 1.5...The Classification of Current Studies on Intelligent Optimization Algorithm; 1.5.1 Algorithm Innovation; 1.5.2 Algorithm Improvement; 1.5.3 Algorithm Hybridization; 1.5.4 Algorithm Parallelization; 1.5.5 Algorithm Application; 1.6...Development Trends; 1.6.1 Intellectualization; 1.6.2 Service-Orientation; 1.6.3 Application-Oriented; 1.6.4 User-Centric; 1.7...Summary; References; 2 Recent Advances of Intelligent Optimization Algorithm in Manufacturing; 2.1...Introduction
  • 2.2...Classification of Optimization Problems in Manufacturing2.2.1 Numerical Function Optimization; 2.2.2 Parameter Optimization; 2.2.3 Detection and Classification; 2.2.4 Combinatorial Scheduling; 2.2.5 Multi-disciplinary Optimization; 2.2.6 Summary of the Five Types of Optimization Problems in Manufacturing; 2.3...Challenges for Addressing Optimization Problems in Manufacturing; 2.3.1 Balance of Multi-objectives; 2.3.2 Handling of Multi-constraints; 2.3.3 Extraction of Priori Knowledge; 2.3.4 Modeling of Uncertainty and Dynamics; 2.3.5 Transformation of Qualitative and Quantitative Features
  • 2.3.6 Simplification of Large-Scale Solution Space2.3.7 Jumping Out of Local Convergence; 2.4...An Overview of Optimization Methods in Manufacturing; 2.4.1 Empirical-Based Method; 2.4.2 Prediction-Based Method; 2.4.3 Simulation-Based Method; 2.4.4 Model-Based Method; 2.4.5 Tool-Based Method; 2.4.6 Advanced-Computing-Technology-Based Method; 2.4.7 Summary of Studies on Solving Methods; 2.5...Intelligent Optimization Algorithms for Optimization Problems in Manufacturing; 2.6...Challenges of Applying Intelligent Optimization Algorithms in Manufacturing; 2.6.1 Problem Modeling
  • 2.6.2 Algorithm Selection2.6.3 Encoding Scheming; 2.6.4 Operator Designing; 2.7...Future Approaches for Manufacturing Optimization; 2.8...Future Requirements and Trends of Intelligent Optimization Algorithm in Manufacturing; 2.8.1 Integration; 2.8.2 Configuration; 2.8.3 Parallelization; 2.8.4 Executing as Service; 2.9...Summary; References; Part IIDesign and Implementation; 3 Dynamic Configuration of Intelligent Optimization Algorithms; 3.1...Concept and Mainframe of DC-IOA; 3.1.1 Mainframe of DC-IOA; 3.1.2 Problem Specification and Construction of Algorithm Library in DC-IOA; 3.2...Case Study
Control code
SPR889942592
Dimensions
unknown
Extent
1 online resource (xiii, 361 pages)
File format
unknown
Form of item
online
Isbn
9783319088402
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other control number
10.1007/978-3-319-08840-2
Other physical details
illustrations (some color).
Quality assurance targets
not applicable
Reformatting quality
unknown
Reproduction note
Electronic resource.
Sound
unknown sound
Specific material designation
remote

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