Cellular Evolutionary Algorithms Site

Book
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Cellular Genetic Algorithms
E. Alba, B. Dorronsoro
Series: Ops. Res./Computer Science
Vol. 42
250 p.
2008
Springer-Verlag
ISBN: 978-0-387-77609-5
Table of Contents | Buy it!
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Structure of cEAs

Typical pseudocode for a cEA
Operators of cEAs

Selection
Reproduction
      Recombination
      Mutation
      Reordering
Replacement

Structure of individuals
The neighborhood
The concept of ratio

Recent Research in cEAs

   Modeling the Selection Pressure

      Takeover Time

   The Exploration/Exploitation Balance

      Synchronous vs. asynchronous cEAs
      Varying the population density
      Changing the ratio during the evolution
      The predator-prey model

   Parallelizing cEAs

      SIMD machines
      MIMD machines
      Some more recent models

   Measures of evolution in cEAs

   cEAs for Solving Complex Problems

      Satisfiability problem - SAT
      Vehicle Routing Problem - VRP
      Error Correcting Codes design problem - ECC
      cGAs for training recurrent neural networks (under construction)
      cGP for data classification (under construction)

What Cellular Evolutionary Algorithms (cEAs) are?

Introduction to cEAs
cEAs classification

Evolutionary Programming (EP)
Evolution Strategies (ES)
Genetic Algorithms (GA)
Genetic Programming (GP)

References

Bibliography
Links

Bernabé Dorronsoro
September , 2004