Grouping Genetic Algorithms

Advances and Applications

Business & Finance, Management & Leadership, Operations Research, Nonfiction, Computers, Advanced Computing, Artificial Intelligence, General Computing
Cover of the book Grouping Genetic Algorithms by Charles Mbohwa, Michael Mutingi, Springer International Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Charles Mbohwa, Michael Mutingi ISBN: 9783319443942
Publisher: Springer International Publishing Publication: October 4, 2016
Imprint: Springer Language: English
Author: Charles Mbohwa, Michael Mutingi
ISBN: 9783319443942
Publisher: Springer International Publishing
Publication: October 4, 2016
Imprint: Springer
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

More books from Springer International Publishing

Cover of the book Iatrogenic Effects of Orthodontic Treatment by Charles Mbohwa, Michael Mutingi
Cover of the book Nanoscale Insights into Ion-Beam Cancer Therapy by Charles Mbohwa, Michael Mutingi
Cover of the book Integration of Nature and Technology for Smart Cities by Charles Mbohwa, Michael Mutingi
Cover of the book Resources for Teaching Mindfulness by Charles Mbohwa, Michael Mutingi
Cover of the book Service-Oriented and Cloud Computing by Charles Mbohwa, Michael Mutingi
Cover of the book Diseases of the Central Airways by Charles Mbohwa, Michael Mutingi
Cover of the book Cosmetic Breast Cases by Charles Mbohwa, Michael Mutingi
Cover of the book Money, Commerce, and Economics in Late Medieval English Literature by Charles Mbohwa, Michael Mutingi
Cover of the book Dynamic Parameter Adaptation for Meta-Heuristic Optimization Algorithms Through Type-2 Fuzzy Logic by Charles Mbohwa, Michael Mutingi
Cover of the book International Performance Research Pedagogies by Charles Mbohwa, Michael Mutingi
Cover of the book Ageing and the Built Environment in Singapore by Charles Mbohwa, Michael Mutingi
Cover of the book Heat Pipe Design and Technology by Charles Mbohwa, Michael Mutingi
Cover of the book Time-Symmetry Breaking in Turbulent Multi-Particle Dispersion by Charles Mbohwa, Michael Mutingi
Cover of the book On the Inside of a Marble by Charles Mbohwa, Michael Mutingi
Cover of the book Macular Dystrophies by Charles Mbohwa, Michael Mutingi
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy