
Bioinspired Computation in Combinatorial Optimization by Frank Neumann
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.-
Robot Evolution
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An Introduction to Metaheuristics for Optimization
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Deep Neural Evolution
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Lectures on Intelligent Systems
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Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms
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Coevolutionary Computation and Its Applications
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Visions of DNA Nanotechnology at 40 for the Next 40
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Cartesian Genetic Programming
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Self-organising Software
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Swarm Intelligence
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Evolution as Computation
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Algorithmic Bioprocesses
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General-Purpose Optimization Through Information Maximization
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Nature Inspired Optimisation for Delivery Problems
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Experimental Research in Evolutionary Computation
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Hyper-Heuristics: Theory and Applications
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Modelling in Molecular Biology
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Advances in Metaheuristics for Hard Optimization
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Foraging-Inspired Optimisation Algorithms
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Mobility in Process Calculi and Natural Computing
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Automating the Design of Data Mining Algorithms
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Contemporary Evolution Strategies
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Theory and Principled Methods for the Design of Metaheuristics
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Discrete and Topological Models in Molecular Biology
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Massively Parallel Evolutionary Computation on GPGPUs
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Multimodal Optimization by Means of Evolutionary Algorithms
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Computation in Living Cells
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Sensitivity Analysis for Neural Networks
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Reservoir Computing
“A very nice and, with respect to the topics treated, a useful contribution to the literatureThe book gives a very appealing introduction into the area of bio-inspired algorithms with solid results on the theoretical side, gathering many recent results which so far only have been available in research papers. … recommendable resource both for researchers who want to learn more on the topic and for preparing a course on bio-inspired algorithms. … Altogether this is a very recommendable textbook.” (Klaus Meer, Mathematical Reviews, February, 2015)
"This timely book will be useful to many researchers and advanced undergraduate and graduate students. The key strength of the book is the complexity analysis of the algorithms for a variety of combinatorial optimization problems on graphs. Furthermore, it provides a comprehensive treatment of evolutionary algorithms and ant colony optimization. The book is recommended to anyone working in the areas of computational complexity, combinatorial optimization, and engineering." (Manish Gupta, Computing Reviews, May, 2011)
“This book treats bio-inspired computing methods as stochastic algorithms and presents rigorous results on their runtime behavior. The book is meant to give researchers a state-of-the-art presentation of theoretical results on bio-inspired computing methods in the context of combinatorial optimization. It can be used as basic material for courses on bio-inspired computing that are meant for graduate students and advanced undergraduates.” (I. N. Katz, Zentralblatt MATH, Vol. 1223, 2011)
| SKU | Unavailable |
| ISBN 13 | 9783642265846 |
| ISBN 10 | 3642265847 |
| Title | Bioinspired Computation in Combinatorial Optimization |
| Author | Frank Neumann |
| Series | Natural Computing Series |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Springer |
| Year published | 2013-01-02 |
| Number of pages | 216 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |

































