An Introduction to Genetic Algorithms - Boente
An Introduction to Genetic Algorithms - Boente
An Introduction to Genetic Algorithms - Boente
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Defining ri,j(k) and is somewhat tricky. Vose and Liepins first defined a simpler matrix M whose<br />
elements Mi,j give the probability ri,j(0) that string 0 (i.e., the string of all zeros) will be produced by a<br />
recombination event between string i and string j, given that i and j are selected <strong>to</strong> mate. I will go through this<br />
construction in detail so readers less familiar with probability theory can see how such constructions are done.<br />
(Other readers may wish <strong>to</strong> attempt it themselves before reading the following.) Once ri,j(0) is defined, it can<br />
be used in a clever way <strong>to</strong> define the general case.<br />
The expression for ri,j(0) is equal <strong>to</strong> the sum of two terms: the probability that crossover does not occur<br />
between i and j and the selected offspring (i or j) is mutated <strong>to</strong> all zeros (first term) and the probability that<br />
crossover does occur and the selected offspring is mutated <strong>to</strong> all zeros (second term).<br />
If i and j are selected <strong>to</strong> mate, the probability that crossover occurs between them is pc and the probability that<br />
it does not occur is 1 p c. Likewise, the probability that mutation occurs at each bit in the selected offspring<br />
is pm and the probability that it does not occur is 1 p m. If | i| is the number of ones in a string iof length l, the<br />
probability that i will be mutated <strong>to</strong> all zeros is the probability that all of the |i| ones will be mutated times the<br />
probability that none of the (l |i|) zeros will be mutated:<br />
The first term in the expression for ri,j(0) translates <strong>to</strong><br />
Recall that, in this model, only one offspring is selected for the next population. The fac<strong>to</strong>r ½ indicates that<br />
each of the two offspring has equal probability of being selected.<br />
For the second term, let h and k denote the two offspring produced from a crossover at point c(counted from<br />
the right−hand side of the string; see figure 4.3). Note that there are l 1 possible crossover points, so the<br />
probability of choosing point c is 1/(l 1). The second term can then be written as<br />
Figure 4.3: Illustration of c, i1, i2, j1, and j2.<br />
Chapter 4: Theoretical Foundations of <strong>Genetic</strong> <strong>Algorithms</strong><br />
Again, the fac<strong>to</strong>r 1/2 indicates that one of the two offspring is selected, with equal probability for each.<br />
To complete this, we need only the expressions for |h| and |k|. Let i1 be the substring of i consisting of the l c<br />
bits <strong>to</strong> the left of point c, let i2 be the substring consisting of the c bits <strong>to</strong> the right of point c, and let j1 and j2<br />
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