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Home 2015 › Forums › Numerical Method › Optimization › Differential Evolution
Tagged: genetic algo, portfolio optimization
This topic contains 0 replies, has 1 voice, and was last updated by jose123456789 8 months, 1 week ago.
Hello guys : I am testing the differential evolution class:
I have a very large basket (a qquadratic problem) that I want to optmize subject to contraints:
equal, greater and less than.
When I run the optimization using other methods (no diffwerential evoution) I get convergence but
it can take 30 minutes to run for 1400 tickers.
I want to give Genetic Algo a try to find optimal value opf weights.
basically I want to know how to set up the problem correctly, please point me in the right direction.
what do I have to correct i the definition below?
——————————————————————————————–
QPProblem problem = new QPProblem(F, equal, greater, less);
DEOptim solver = new DEOptim(new DEOptim.NewCellFactory() {
@Override
public DEOptimCellFactory newCellFactory() {
return new IntegralConstrainedCellFactory(new Rand1Bin(0.5, 0.5, uniform), new IntegralConstrainedCellFactory.AllIntegers());
}
}, uniform, 0.00001, 400000, 100);
IterativeSolution soln = solver.solve(problem);
————————————————————————–
I wonder if you could be so kind to point me out in the right direction.
How can I define the problem in suach a way that that the minumum is a vector of real numbers
respecting the inequalitiers (equal, less and greater)
Do u have more examples illustrating the differential evolution class in algoquant? (besides the integer optimization of cross over strategy)
Thank you,
ja
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