<DIV>Hallo </DIV>
<DIV> </DIV>
<DIV>I have treid to minimize an objective function (f_obj) using SigmaTruncationScaling by puting multiplying the objective function by -1. It goes OK. </DIV>
<DIV>I like to use my own scaling which I think it will better for minimization of my objective function. The scaling I propose is that:</DIV>
<DIV>fittness(i)= exp[ [max( f_obj(i)) - f_obj(i))] * 5 / [max( f_obj(i)) - min( f_obj(i)) ] ]</DIV>
<DIV> </DIV>
<DIV>I use this scaling, because I expect to work better than SigmaTruncationScaling </DIV>
<DIV>the follwoing c++ prototype (code) was added to GAScaling.c file, however the results was not satisfied. The result shows divergence contradicting of what expected. I s there any thing wrong? What are the steps of writing my own scaling. </DIV>
<DIV> </DIV>
<DIV>#if USE_EXPON_SCALING == 1<BR>/* ----------------------------------------------------------------------------<BR>ExponScaling<BR>---------------------------------------------------------------------------- */<BR>// This is an a test scaling<BR>void GAExponScaling::evaluate(const GAPopulation & p) {<BR> for(int i=0; i<p.size(); i++){<BR> double ffup = (double)(p.max())-(double)(p.individual(i).score());<BR> double ffdown = (double)(p.max())-(double)(p.min());<BR> double f= exp(ffup*5.0/ffdown);<BR> if(f < 0) f = 0.0;<BR> p.individual(i).fitness((float)f); </DIV>
<DIV> }<BR>}<BR>#endif</DIV>
<DIV> </DIV>
<DIV> </DIV>
<DIV>thanks</DIV>
<DIV> </DIV>
<DIV> </DIV><p>
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