---- We apologize for multiple postings ----
Dear colleague,
We are pleased to announce a new book:
******************************************
CELLULAR GENETIC ALGORITHMS
E. Alba, B. Dorronsoro
Series: Operations Research/Computer Science
Vol. 42
250 p.
2008
Springer-Verlag
ISBN: 978-0-387-77609-5
******************************************
Cellular Genetic Algorithms define a new class of optimization
algorithms based on the concepts of structured populations and Genetic
Algorithms (GAs). The authors explain and demonstrate the validity of
these cellular genetic algorithms throughout the book. This class of
genetic algorithms is shown to produce impressive results on a whole
range of domains, including complex problems that are epistatic, multi-
modal, deceptive, discrete, continuous, multi-objective, and random in
nature. The focus of this book is twofold. On the one hand, the
authors present new algorithmic models and extensions to the basic
class of Cellular GAs in order to tackle complex problems more
efficiently. On the other hand, practical real world tasks are
successfully faced by applying Cellular GA methodologies to produce
workable solutions of real-world applications. These methods can
include local search (memetic algorithms), cooperation, parallelism,
multi-objective, estimations of distributions, and self-adaptive ideas
to extend their applicability.
The methods are benchmarked against well-known metaheutistics like
Genetic Algorithms, Tabu Search, heterogeneous GAs, Estimation of
Distribution Algorithms, etc. Also, a publicly available software tool
is offered to reduce the learning curve in applying these techniques.
The three final chapters will use the classic problem of “vehicle
routing” and the hot topics of “ad-hoc mobile networks” and “DNA
genome sequencing” to clearly illustrate and demonstrate the power and
utility of these algorithms.
TABLE OF CONTENTS
Part I. Introduction
1. Introduction to Cellular Genetic Algorithms
2. The State of the Art in Cellular Evolutionary Algorithms
Part II. Characterizing Cellular Genetic Algorithms
3. On the Effects of Structuring the Population
4. Some Theory: A Selection Pressure Study on cGAs
Part III. Algorithmic Models and Extensions
5. Algorithmic and Experimental Design
6. Design of Self-adaptive cGAs
7. Design of Cellular Memetic Algorithms
8. Design of Parallel Cellular Genetic Algorithms
9. Designing Cellular Genetic Algorithms for Multi-objective
Optimization
10. Other Cellular Models
11. Software for cGAs: The JCell Framework
Part IV. Applications of cGAs
12. Continuous Optimization
13. Logistics: The Vehicle Routing Problem
14. Telecommunications: Optimization of the Broadcasting Process in
MANETs
15. Bioinformatics: The DNA Fragment Assembly Problem
Part V. Appendix
A. Definition of the Benchmark Problem
Bernabé Dorronsoro, PhD
Scientific Collaborator
University of Luxembourg
[EMAIL PROTECTED]
T +352 4666445619
F +352 4666445620
_______________________________________________
uai mailing list
uai@ENGR.ORST.EDU
https://secure.engr.oregonstate.edu/mailman/listinfo/uai
