Overview
- Accessible introduction, suitable for students and for self-study
- Assumes basic computing skills only as a prerequisite
- Authors are interdisciplinary researchers, and they bring this into their approach
Part of the book series: Natural Computing Series (NCS)
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Table of contents (12 chapters)
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Front Matter
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Back Matter
Keywords
About this book
The authors stress the relative simplicity, efficiency, flexibility of use, and suitability of various approaches used to solve difficult optimization problems. The authors are experienced, interdisciplinary lecturers and researchers and in their explanations they demonstrate many shared foundational concepts among the key methodologies.
This textbook is a suitable introduction for undergraduate and graduate students, researchers, and professionals in computer science, engineering, and logistics.
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Authors and Affiliations
About the authors
Bastien Chopard is a professor in the Département d'informatique of the Université de Genève, where he directs the Scientific and Parallel Computing Group. His main research activity concerns the study of complex systems, in particular the development of new numerical methods to model and simulate phenomena in natural sciences, economics, social systems, and biomedical applications, the key tools used being cellular automata, the lattice Boltzmann method, and multiagent techniques.
Marco Tomassini is an honorary professor at the Faculty of Business and Economics of the University of Lausanne (HEC). After obtaining a PhD degree in Theoretical Chemistry working on computer simulations of condensed matter systems, he switched to Computer Science and complex systems investigations. His main research activities have since focused on parallel computing, cellular automata, evolutionary algorithms, the structure of difficult problem landscapes, complex networks, and evolutionary games.
Bibliographic Information
Book Title: An Introduction to Metaheuristics for Optimization
Authors: Bastien Chopard, Marco Tomassini
Series Title: Natural Computing Series
DOI: https://doi.org/10.1007/978-3-319-93073-2
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2018
Hardcover ISBN: 978-3-319-93072-5Published: 13 November 2018
eBook ISBN: 978-3-319-93073-2Published: 02 November 2018
Series ISSN: 1619-7127
Series E-ISSN: 2627-6461
Edition Number: 1
Number of Pages: XII, 226
Number of Illustrations: 44 illustrations in colour
Topics: Artificial Intelligence, Optimization, Computational Intelligence, Operations Research/Decision Theory, Theory of Computation