Differential Evolution

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    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() {
    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,

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