One of the main difficulties of applying an evolutionary algorithm (or, as a matter of fact, any heuristic method) to a given problem is to decide on an appropriate set of parameter values. Typically these are specified before the algorithm is run and include population size, selection rate, operator probabilities, not to mention the representation and the operators themselves.
This book gives the reader a solid perspective on the different approaches that have been proposed to automate control of these parameters as well as understanding their interactions. The book covers a broad area of evolutionary computation, including genetic algorithms, evolution strategies, genetic programming, estimation of distribution algorithms, and also discusses the issues of specific parameters used in parallel implementations, multi-objective evolutionary algorithms, and practical consideration for real-world applications.
It is a recommended read for researchers and practitioners of evolutionary computation and heuristic methods.
| ISBN: | 9783540694311 |
| Publication date: | 16th March 2007 |
| Author: | Fernando G Lobo, Cláudio F Lima, Zbigniew Michalewicz |
| Publisher: | Springer an imprint of Springer Berlin Heidelberg |
| Format: | Hardback |
| Pagination: | 317 pages |
| Series: | Studies in Computational Intelligence |
| Genres: |
Maths for engineers Artificial intelligence |
One of the main difficulties of applying an evolutionary algorithm (or, as a matter of fact, any heuristic method) to a given problem is to decide on an appropriate set of parameter values. Typically these are specified before the algorithm is run and include population size, selection rate, operator probabilities, not to mention the representation and the operators themselves.
Parameter Setting in Evolutionary Algorithms features in the following genres: Maths for engineers, Artificial intelligence
Hardback. Not Available.
Parameter Setting in Evolutionary Algorithms was written by Fernando G Lobo, Cláudio F Lima, Zbigniew Michalewicz and published by Springer an imprint of Springer Berlin Heidelberg
Parameter Setting in Evolutionary Algorithms has 317 pages
Yes it is part of Studies in Computational Intelligence series