- Intermediate Crossover
             (HC/IC)

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Read also
● Voigt H.-M. , Mühlenbein H. , (1995), Cvetković D. , Fuzzy recombination for the Breeder Genetic Algorithm, in Proceedings of the Sixth International Conference on Genetic Algorithms, Morgan Kaufman, pp. 104-111
WEB:     http://citeseer.ifi.unizh.ch/voigt95fuzzy.html
            http://citeseer.ist.psu.edu/voigt95fuzzy.html
            http://www.amspr.gfai.de/publications_de.htm
●   Mühlenbein H. , Schlierkamp-Voosen D.  (1993), Predictive Models for the Breeder Genetic Algorithm I. Continuous Parameter Optimization, in Evolutionary Computation, vol. 1, pp. 25-49
WEB:     http://citeseer.ifi.unizh.ch/mtihlenbein93predictive.html
            http://citeseer.ist.psu.edu/mtihlenbein93predictive.html
            http://www.ais.fhg.de/~muehlen/pegasus/publications.html
●   Herrera F. , Lozano M. , Verdegay J.L.  (1998), Tackling Real-Coded Genetic Algorithms: Operators and Tools for Behavioural Analysis, in Artificial Intelligence Review, Kluwer, vol. 12, pp. 254-319
WEB:     http://citeseer.ifi.unizh.ch/herrera98tackling.html
            http://citeseer.ist.psu.edu/herrera98tackling.html

Algorithm
1.     select two parents X^(t) and Y^(t) from a parent pool

2.     create one offspring  X^(t+1)  as follows:

3.              for i = 1 to n do

4.              assume that x_i^(t)≤y_i^(t)

5.              choose a uniform random real number w from interval <0,1>

6.              x_i^(t+1)=x_i^(t)+w(y_i^(t)-x_i^(t))

7.              end do  

Comments
Parameter w may be of constant value equal to 0.5 or may be selected by a draw from interval <0,1> (row: 5).