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C. FERREIRA In Leandro N. de Castro and Fernando J. Von Zuben, eds., Recent Developments in Biologically Inspired Computing, pages 82-103, Idea Group Publishing, 2004.

Gene Expression Programming and the Evolution of Computer Programs

Two-point Recombination
 

In two-point recombination two parent chromosomes are paired and two points are randomly chosen as crossover points. The material between the recombination points is afterwards exchanged between the parent chromosomes, forming two new daughter chromosomes.

Consider the following pair of recombining chromosomes:

012345678901201234567890120123456789012
/bQbb*aabaaaaQ*a/b+bbbaaabQ+/aa+babaabb

+-Qa/Qaabbaba+Q-+/+abbbaaa//+-/+bababab

Suppose bond 7 in gene 1 (between positions 6 and 7) and bond 4 in gene 3 (between positions 3 and 4) were chosen as crossover points. Then, the following daughter chromosomes are created:

012345678901201234567890120123456789012
/bQbb*aabbaba+Q-+/+abbbaaa//+-a+babaabb

+-Qa/QaabaaaaQ*a/b+bbbaaabQ+/a/+bababab

It is worth emphasizing that two-point recombination is more disruptive than one-point recombination in the sense that it recombines the genetic material more thoroughly, constantly destroying old building blocks and creating new ones. But like one-point recombination, two-point recombination has also a conservative side and it is good at swapping entire genes and open reading frames. And, as observed for one-point recombination, two-point recombination can also give rise to duplicated genes if it were used together with gene transposition.

Notwithstanding, if the goal is to evolve good solutions, one-point or two-point recombination should never be used as the only source of genetic variation as they tend to homogenize populations (Ferreira 2002c). However, together with mutation, inversion and transposition, these operators are an excellent source of genetic variation and are more than sufficient to evolve good solutions to virtually all problems.

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