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" Bioinspired computation in combinatorial optimization : "
Frank Neumann, Carsten Witt.
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BL
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| Record Number
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982442
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b736812
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| Main Entry
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Neumann, Frank, (Computer scientist)
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| Title & Author
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Bioinspired computation in combinatorial optimization : : algorithms and their computational complexity /\ Frank Neumann, Carsten Witt.
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| Publication Statement
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Berlin ;Heidelberg :: Springer,, ©2010.
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| Series Statement
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Natural computing series
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| Page. NO
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1 online resource (xii, 216 pages)
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| ISBN
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3642165435
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: 3642165443
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: 3642165451
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: 3642265847
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: 9783642165436
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: 9783642165443
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: 9783642165450
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: 9783642265846
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9783642165436
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| Bibliographies/Indexes
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Includes bibliographical references.
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| Contents
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pt. 1. Basics -- pt. 2. Single-objective optimization -- pt. 3. Multi-objective optimization.
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| Abstract
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Bioinspired computation methods, such as evolutionary algorithms and ant colony optimization, are being applied successfully to complex engineering and combinatorial optimization problems, and it is very important that we understand the computational complexity of these search heuristics. This is the first book to explain the most important results achieved in this area. The authors show how runtime behavior can be analyzed in a rigorous way. in particular for combinatorial optimization. They present well-known problems such as minimum spanning trees, shortest paths, maximum matching, and covering and scheduling problems. Classical single-objective optimization is examined first. They then investigate the computational complexity of bioinspired computation applied to multiobjective variants of the considered combinatorial optimization problems, and in particular they show how multiobjective optimization can help to speed up bioinspired computation for single-objective optimization problems. This book will be valuable for graduate and advanced undergraduate courses on bioinspired computation, as it offers clear assessments of the benefits and drawbacks of various methods. It offers a self-contained presentation, theoretical foundations of the techniques, a unified framework for analysis, and explanations of common proof techniques, so it can also be used as a reference for researchers in the areas of natural computing, optimization and computational complexity.
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| Subject
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Combinatorial optimization.
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Natural computation.
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Combinatorial optimization.
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Informatique.
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Natural computation.
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| Dewey Classification
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519.6/4
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| LC Classification
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QA402.5.N48 2010
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| Added Entry
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Witt, Carsten.
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