Grouping genetic algorithms : advances and applications /: advances and applications. ([2016])
- Record Type:
- Book
- Title:
- Grouping genetic algorithms : advances and applications /: advances and applications. ([2016])
- Main Title:
- Grouping genetic algorithms : advances and applications
- Further Information:
- Note: Michael Mutingi, Charles Mbohwa.
- Authors:
- Mutingi, Michael
Mbohwa, Charles - Contents:
- Intro; Preface; Contents; Introduction; 1 Exploring Grouping Problems in Industry; 1.1 Introduction; 1.2 Identifying Grouping Problems in Industry; 1.2.1 Cell Formation in Manufacturing Systems; 1.2.2 Assembly Line Balancing; 1.2.3 Job Shop Scheduling; 1.2.4 Vehicle Routing Problem; 1.2.5 Home Healthcare Worker Scheduling; 1.2.6 Bin Packing Problem; 1.2.7 Task Assignment Problem; 1.2.8 Modular Product Design; 1.2.9 Group Maintenance Planning; 1.2.10 Order Batching; 1.2.11 Team Formation; 1.2.12 Earnings Management; 1.2.13 Economies of Scale; 1.2.14 Timetabling 1.2.15 Student Grouping for Cooperative Learning1.2.16 Other Problems; 1.3 Extant Modeling Approaches to Grouping Problems; 1.4 Structure of the Book; References; 2 Complicating Features in Industrial Grouping Problems; 2.1 Introduction; 2.2 Research Methodology; 2.3 Research Findings; 2.4 Complicating Features; 2.4.1 Model Conceptualization; 2.4.2 Myriad of Constraints; 2.4.2.1 Intra-Group Relationship; 2.4.2.2 Inter-Group Relationship; 2.4.2.3 Group Size Limits; 2.4.2.4 Grouping Limit; 2.4.3 Fuzzy Management Goals; 2.4.4 Computational Complexity; 2.5 Suggested Solution Approaches 2.6 SummaryReferences; Grouping Genetic Algorithms; 3 Grouping Genetic Algorithms: Advances for Real-World Grouping Problems; 3.1 Introduction; 3.2 Grouping Genetic Algorithm: An Overview; 3.2.1 Group Encoding; 3.3 Crossover; 3.3.1 Mutation; 3.3.2 Inversion; 3.4 Grouping Genetic Algorithms: Advances and Innovations; 3.4.1 Group EncodingIntro; Preface; Contents; Introduction; 1 Exploring Grouping Problems in Industry; 1.1 Introduction; 1.2 Identifying Grouping Problems in Industry; 1.2.1 Cell Formation in Manufacturing Systems; 1.2.2 Assembly Line Balancing; 1.2.3 Job Shop Scheduling; 1.2.4 Vehicle Routing Problem; 1.2.5 Home Healthcare Worker Scheduling; 1.2.6 Bin Packing Problem; 1.2.7 Task Assignment Problem; 1.2.8 Modular Product Design; 1.2.9 Group Maintenance Planning; 1.2.10 Order Batching; 1.2.11 Team Formation; 1.2.12 Earnings Management; 1.2.13 Economies of Scale; 1.2.14 Timetabling 1.2.15 Student Grouping for Cooperative Learning1.2.16 Other Problems; 1.3 Extant Modeling Approaches to Grouping Problems; 1.4 Structure of the Book; References; 2 Complicating Features in Industrial Grouping Problems; 2.1 Introduction; 2.2 Research Methodology; 2.3 Research Findings; 2.4 Complicating Features; 2.4.1 Model Conceptualization; 2.4.2 Myriad of Constraints; 2.4.2.1 Intra-Group Relationship; 2.4.2.2 Inter-Group Relationship; 2.4.2.3 Group Size Limits; 2.4.2.4 Grouping Limit; 2.4.3 Fuzzy Management Goals; 2.4.4 Computational Complexity; 2.5 Suggested Solution Approaches 2.6 SummaryReferences; Grouping Genetic Algorithms; 3 Grouping Genetic Algorithms: Advances for Real-World Grouping Problems; 3.1 Introduction; 3.2 Grouping Genetic Algorithm: An Overview; 3.2.1 Group Encoding; 3.3 Crossover; 3.3.1 Mutation; 3.3.2 Inversion; 3.4 Grouping Genetic Algorithms: Advances and Innovations; 3.4.1 Group Encoding Strategies; 3.4.1.1 Encoding Strategy 1; 3.4.1.2 Encoding Strategy 2; 3.4.2 Initialization; 3.4.2.1 User-Generated Seeds; 3.4.2.2 Random Generation; 3.4.2.3 Constructive Heuristics; 3.4.3 Selection Strategies; 3.4.3.1 Stochastic Sampling Without Replacement 3.4.4 Rank-Based Wheel Selection Strategy3.4.5 Crossover Strategies; 3.4.5.1 Two-Point Group Crossover; 3.4.5.2 Adaptive Crossover; 3.4.6 Mutation Strategies; 3.4.6.1 Swap Mutation; 3.4.6.2 Split Mutation; 3.4.6.3 Merge Mutation; 3.4.6.4 Adaptive Mutation; 3.4.7 Inversion; 3.4.7.1 Two-Point Inversion; 3.4.7.2 Single-Point Inversion; 3.4.7.3 Adaptive Inversion; 3.4.8 Replacement Strategies; 3.4.9 Termination Strategies; 3.4.9.1 Iteration Count (ItCount); 3.4.9.2 Iterations Without Improvement (ItWithoutImp); 3.4.9.3 Hybrid Criteria; 3.5 Application Areas; 3.6 Summary; References 4 Fuzzy Grouping Genetic Algorithms: Advances for Real-World Grouping Problems4.1 Introduction; 4.2 Preliminaries: Fuzzy Logic Control; 4.3 Fuzzy Grouping Genetic Algorithms: Advances and Innovations; 4.3.1 FGGA Coding Scheme; 4.3.2 Initialization; 4.3.3 Fuzzy Fitness Evaluation; 4.3.3.1 Multifactor Evaluation; 4.3.3.2 Fuzzy Goal-Oriented Fitness Evaluation; 4.3.4 Fuzzy Genetic Operators; 4.3.4.1 Fuzzy Controlled Genetic Parameters; Convergence Measure; Diversity Measure; Crossover Probability; Mutation Probability; Inversion Probability; 4.3.4.2 Fuzzy Logic Controlled Crossover … (more)
- Publisher Details:
- Cham, Switzerland : Springer
- Publication Date:
- 2016
- Copyright Date:
- 2017
- Extent:
- 1 online resource (xiv, 243 pages), illustrations
- Subjects:
- 519.6/25
Engineering
Genetic algorithms
Genetic algorithms
Business & Economics -- Operations Research
Computers -- Intelligence (AI) & Semantics
Technology & Engineering -- Industrial Engineering
Operational research
Artificial intelligence
Production engineering
Operations research
Artificial intelligence
Industrial engineering
Electronic books - Languages:
- English
- ISBNs:
- 9783319443942
3319443941 - Related ISBNs:
- 9783319443935
- Notes:
- Note: Includes bibliographical references and index.
Note: Online resource; title from PDF title page (SpringerLink, viewed October 14, 2016). - Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
- Access Usage:
- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
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- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.363767
- Ingest File:
- 01_332.xml