Studies in Computational Intelligence

Grouping Genetic Algorithms

Advances and Applications

Authors: Mutingi, Michael, Mbohwa, Charles

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  • Treats problems from a spectrum of industrial disciplines as easy-to-understand and solve grouping structures
  • Schematics, flow charts and algorithmic descriptions render the content easy to digest
  • Shows the reader new efficient heuristic grouping techniques
  • Illustrative computational examples demonstrate the effectiveness of the algorithm, even in a fuzzy problem environment
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eBook $129.00
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  • ISBN 978-3-319-44394-2
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Hardcover $169.99
price for USA in USD
  • ISBN 978-3-319-44393-5
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  • Usually dispatched within 3 to 5 business days.
Softcover $169.99
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  • ISBN 978-3-319-83048-3
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

This book presents advances and innovations in grouping genetic algorithms, enriched with new and unique heuristic optimization techniques. These algorithms are specially designed for solving industrial grouping problems where system entities are to be partitioned or clustered into efficient groups according to a set of guiding decision criteria. Examples of such problems are: vehicle routing problems, team formation problems, timetabling problems, assembly line balancing, group maintenance planning, modular design, and task assignment. A wide range of industrial grouping problems, drawn from diverse fields such as logistics, supply chain management, project management, manufacturing systems, engineering design and healthcare, are presented. Typical complex industrial grouping problems, with multiple decision criteria and constraints, are clearly described using illustrative diagrams and formulations. The problems are mapped into a common group structure that can conveniently be used as an input scheme to specific variants of grouping genetic algorithms. Unique heuristic grouping techniques are developed to handle grouping problems efficiently and effectively. Illustrative examples and computational results are presented in tables and graphs to demonstrate the efficiency and effectiveness of the algorithms.

Researchers, decision analysts, software developers, and graduate students from various disciplines will find this in-depth reader-friendly exposition of advances and applications of grouping genetic algorithms an interesting, informative and valuable resource.


About the authors

Michael Mutingi is a Lecturer and a Researcher in Industrial and Systems Engineering. He researches in healthcare operations management, biologically inspired metaheuristic optimization, fuzzy multi-criteria decision methods, and lean healthcare. Other areas of interest include green supply chain management, logistics management, manufacturing systems simulation, and business system dynamics.

Charles Mbohwa is an established researcher and professor in operations management, manufacturing systems, green supply chain management and sustainability engineering, optimization, and  his specializations include renewable energy systems, and bio-fuel feasibility.

Table of contents (13 chapters)

  • Exploring Grouping Problems in Industry

    Mutingi, Michael (et al.)

    Pages 3-29

  • Complicating Features in Industrial Grouping Problems

    Mutingi, Michael (et al.)

    Pages 31-42

  • Grouping Genetic Algorithms: Advances for Real-World Grouping Problems

    Mutingi, Michael (et al.)

    Pages 45-66

  • Fuzzy Grouping Genetic Algorithms: Advances for Real-World Grouping Problems

    Mutingi, Michael (et al.)

    Pages 67-86

  • Multi-Criterion Team Formation Using Fuzzy Grouping Genetic Algorithm Approach

    Mutingi, Michael (et al.)

    Pages 89-105

Buy this book

eBook $129.00
price for USA in USD (gross)
  • ISBN 978-3-319-44394-2
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $169.99
price for USA in USD
  • ISBN 978-3-319-44393-5
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $169.99
price for USA in USD
  • ISBN 978-3-319-83048-3
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Grouping Genetic Algorithms
Book Subtitle
Advances and Applications
Authors
Series Title
Studies in Computational Intelligence
Series Volume
666
Copyright
2017
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing Switzerland
eBook ISBN
978-3-319-44394-2
DOI
10.1007/978-3-319-44394-2
Hardcover ISBN
978-3-319-44393-5
Softcover ISBN
978-3-319-83048-3
Series ISSN
1860-949X
Edition Number
1
Number of Pages
XIV, 243
Number of Illustrations
78 b/w illustrations
Topics