Bioinspired Computation in Combinatorial Optimization: Algorithms and Their Computational Complexity / Edition 1

Bioinspired Computation in Combinatorial Optimization: Algorithms and Their Computational Complexity / Edition 1

ISBN-10:
3642165435
ISBN-13:
9783642165436
Pub. Date:
11/04/2010
Publisher:
Springer Berlin Heidelberg
ISBN-10:
3642165435
ISBN-13:
9783642165436
Pub. Date:
11/04/2010
Publisher:
Springer Berlin Heidelberg
Bioinspired Computation in Combinatorial Optimization: Algorithms and Their Computational Complexity / Edition 1

Bioinspired Computation in Combinatorial Optimization: Algorithms and Their Computational Complexity / Edition 1

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Overview

Bioinspired computation methods such as evolutionary algorithms and ant colony optimization are being applied successfully to complex engineering problems and to problems from combinatorial optimization, and with this comes the requirement to more fully understand the computational complexity of these search heuristics. This is the first textbook covering the most important results achieved in this area.

The authors study the computational complexity of bioinspired computation and show how runtime behavior can be analyzed in a rigorous way using some of the best-known combinatorial optimization problems — minimum spanning trees, shortest paths, maximum matching, covering and scheduling problems. A feature of the book is the separate treatment of single- and multiobjective problems, the latter a domain where the development of the underlying theory seems to be lagging practical successes.

This book will be very valuable for teaching courses on bioinspired computation and combinatorial optimization. Researchers will also benefit as the presentation of the theory covers the most important developments in the field over the last 10 years. Finally, with a focus on well-studied combinatorial optimization problems rather than toy problems, the book will also be very valuable for practitioners in this field.


Product Details

ISBN-13: 9783642165436
Publisher: Springer Berlin Heidelberg
Publication date: 11/04/2010
Series: Natural Computing Series
Edition description: 2010
Pages: 216
Product dimensions: 6.30(w) x 9.20(h) x 0.80(d)

About the Author

Authors have given tutorials on this topic at major international conferences

Table of Contents

Basics.- Combinatorial Optimization and Computational Complexity.- Shastic Search Algorithms.- Analyzing Shastic Search Algorithms.- Single-objective Optimization.- Minimum Spanning Trees.- Maximum Matchings.- Makespan Scheduling.- Shortest Paths.- Eulerian Cycles.- Multi-objective Optimization.- Multi-objective Minimum Spanning Trees.- Minimum Spanning Trees Made Easier.- Covering Problems.- Cutting Problems.

What People are Saying About This

From the Publisher

"Bioinspired computing is successful in practice. Over the past decade a body of theory for bioinspired computing has been developed. The authors have contributed significantly to this body and give a highly readable account of it." (Kurt Mehlhorn, Max Planck Institute for Informatics, and Saarland University, Germany)

"Bioinspired algorithms belong to the most powerful methods used to tackle real world optimization problems. This book gives such algorithms a solid foundation. It presents some of the most exciting results that have been obtained in bioinspired computing in the last decade." (Zbigniew Michalewicz, University of Adelaide, Australia)

"This book presents a most welcome theoretical computer science approach and perspective to the design and analysis of discrete evolutionary algorithms. It describes the design and derivation of evolutionary algorithms which have precise computation complexity bounds for combinatorial optimization. The book should appeal to researchers and practitioners of evolutionary algorithms and computation who want to learn the state of the art in evolutionary algorithm theory." (Una-May O'Reilly, CSAIL, MIT, USA)

"The evolutionary computation community has been in need of rigorous results concerning the computational complexity of their approaches for decades. This is the first textbook covering such a fundamental topic. It provides an excellent overview of the state of the art in this research area, in terms of both the results obtained and the analytical methods. It is an indispensable book for everyone who is interested in the foundations of evolutionary computation." (Xin Yao, University of Birmingham, UK)

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