Overview
- Recent technique that aims to effectively solve real-world optimization problems
- Presents fundamentals, theory, and applications of hyper-heuristics
- Valuable for researchers, graduate students, and practitioners in the areas of biologically inspired computing, optimization, and operations research
Part of the book series: Natural Computing Series (NCS)
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About this book
This introduction to the field of hyper-heuristics presents the required foundations and tools and illustrates some of their applications. The authors organized the 13 chapters into three parts. The first, hyper-heuristic fundamentals and theory, provides an overview of selection constructive, selection perturbative, generation constructive and generation perturbative hyper-heuristics, and then a formal definition of hyper-heuristics. The chapters in the second part of the book examine applications of hyper-heuristics in vehicle routing, nurse rostering, packing and examination timetabling. The third part of the book presents advanced topics and then a summary of the field and future research directions. Finally the appendices offer details of the HyFlex framework and the EvoHyp toolkit, and then the definition, problem model and constraints for the most tested combinatorial optimization problems.
The book will be of value to graduate students, researchers, and practitioners.
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Keywords
Table of contents (13 chapters)
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Hyper-Heuristics: Fundamentals and Theory
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Applications of Hyper-Heuristics
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Past, Present and Future
Authors and Affiliations
About the authors
Bibliographic Information
Book Title: Hyper-Heuristics: Theory and Applications
Authors: Nelishia Pillay, Rong Qu
Series Title: Natural Computing Series
DOI: https://doi.org/10.1007/978-3-319-96514-7
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2018
Hardcover ISBN: 978-3-319-96513-0Published: 18 October 2018
Softcover ISBN: 978-3-030-07206-3Published: 31 January 2019
eBook ISBN: 978-3-319-96514-7Published: 05 October 2018
Series ISSN: 1619-7127
Series E-ISSN: 2627-6461
Edition Number: 1
Number of Pages: XVII, 130
Topics: Theory of Computation, Computational Intelligence, Artificial Intelligence, Optimization, Operations Research/Decision Theory