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Evolution and Optimum Seeking

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120 <strong>Evolution</strong> Strategies for Numerical Optimization<br />

Step 0: (Initialization)<br />

De ne x (0)<br />

k<br />

x (0)<br />

k<br />

= x (0)<br />

Ek =(x(0)<br />

k1:::x (0)<br />

kn) T for all k = 1(1) :<br />

= x(0) Ek is the vector of the kth parent Ek, suchthat Gj(x (0)<br />

k ) 0 for all k =1(1) <strong>and</strong> all j = 1(1)m:<br />

Set the generation counter g =0:<br />

Step 1: (Mutation)<br />

Generate x (g+1)<br />

`<br />

= x (g+1)<br />

k + z (g + `) <br />

such thatGj(x (g+1)<br />

` ) 0 j =1(1)m ` =1(1)<br />

where k 2 [1 ]<br />

e.g., k =<br />

( if ` = p pinteger<br />

`(mod ) otherwise.<br />

x (g+1)<br />

` = x (g+1)<br />

N`<br />

=(x(g+1) `1 :::x (g+1)<br />

`n ) T is the vector of the `th o spring N`<br />

<strong>and</strong> z (g +`) is a normally distributed r<strong>and</strong>om vector with n components:<br />

Step 2: (Selection)<br />

Sort the x (g+1)<br />

` for all ` = 1(1) so that<br />

F (x (g+1)<br />

`1 ) F (x (g+1)<br />

`2 ) for all `1 = 1(1) `2 = + 1(1)<br />

Assign x (g+2)<br />

k<br />

= x (g+1)<br />

`1 for all k`1 = 1(1) :<br />

Increase the generation counter g g +1:<br />

Go to step 1, unless some termination criterion is ful lled.<br />

What happens in one generation for a (2 , 4) evolution strategy is shown schematically on<br />

the two dimensional contour diagram of a non-linear optimization problem in Figure 5.4.<br />

5.2.2 The Rate of Progress of the (1 , )<strong>Evolution</strong> Strategy<br />

In this section we attempt to obtain approximately the rate of progress of the multimembered,<br />

or ( , ) strategy{at least for = 1. For this purpose the n-dimensional<br />

sphere <strong>and</strong> corridor models, as used by Rechenberg (1973), are employed for calculating<br />

the progress for the (1+1) strategy.<br />

In the two membered evolution strategy ' was the expectation value of the useful<br />

distance covered in each mutation. It is convenient here to de ne the rate in terms of the<br />

number of generations.<br />

' = expectation value k^x ; x (g) k;k^x ; x (g;1) k<br />

where ^x is the vector of the optimum <strong>and</strong> x (g) is the average vector of the parents of<br />

generation g.<br />

From the chosen n-dimensional normal distribution of the r<strong>and</strong>om vector, which has<br />

expectation value zero <strong>and</strong> variance 2 for all independent vector components, the probability<br />

density for going from a point E with vector xE = (xE1:::xEn) T to another

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