dr Tomasz D.Gwiazda
 Assistant Professor

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Contents of e-Book
Index of authors
Index of experiment domains


Standard operators
1-Point Crossover
k-Point Crossover
Shuffle Crossover
Reduced Surrogate Crossover
Uniform Crossover
Highly Disruptive Crossover,Heuristic Uniform Crossover
Average Crossover
Discrete Crossover
Flat Crossover
Heuristic Crossover,Intermediate Crossover
Blend Crossover

Binary coded operators
Random Respectful Crossover
Masked Crossover
1bit Adaptation Crossover
Multivariate Crossover
Homologous Crossover
Count-preserving Crossover
Elitist Crossover
    Shuffle Crossover  




download PDF with first 40 pages
from my latest eBook

if you need more operators click here

Read also
Burkowski F.J.  (1999), Shuffle Crossover and Mutual Information, in Proceedings of the 1999 Congress on Evolutionary Computation, pp. 1574-1580

select two parents A(t) and B(t) from a parent pool

2.     create two offspring  C(t+1)  and D(t+1)  as follows:

3.     randomly shuffle (in the same way) the genes in both parents

4.     randomly choose one crossover point cp from set {1,...,n-1}

5.              for i = 1 to cp do

6.              ci(t+1)=ai(t)

7.              di(t+1)=bi(t)

8.              end do

9.              for i = cp + 1 to n do

10.            ci(t+1)=bi(t)

11.            di(t+1)=ai(t)

12.            end do

13.  unshuffle the genes in both offspring


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