robust optimisation

Discussion in 'Python' started by sh.mojtahedzadeh@gmail.com, Aug 5, 2008.

  1. Guest

    Dear all,

    I have a LP model here as follow:


    Min = .42*x1 + .56*x2 + .70*x3;


    S.t.
    x1 + x2 + x3 = 900;

    x1 <= 400 * y1;
    x2 <= 700 * y2;
    x3 <= 600 * y3;

    30*x1 <= 12500;
    40*x2 <= 20000;
    50*x3 <=15000;

    ..15*x1 + .2*x2 +.15*x3 >= 100;
    ..2*x1 + .05*x2 + .2*x3 >= 100;
    ..25*x1 + .15*x2+ .05*x3 >= 150;

    y1+y2+y3 = 2;


    xi>=0,
    yi=0, if x=o
    yi=1, if x>=o

    The constraints
    ..15*x1 + .2*x2 +.15*x3 >= 100;
    ..2*x1 + .05*x2 + .2*x3 >= 100;
    ..25*x1 + .15*x2+ .05*x3 >= 150;


    have uncertainties in x1, x2, and x3 coefficients. I want to know how
    can I make a robust optimisation model for this LP model?


    for example, if we know that all the coefficients have variations
    about 30%.


    Thank you,
    Shab
     
    , Aug 5, 2008
    #1
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  2. Terry Reedy Guest

    wrote:
    > Dear all,
    >
    > I have a LP model here as follow:
    >
    >...
    > The constraints
    > .15*x1 + .2*x2 +.15*x3 >= 100;
    > .2*x1 + .05*x2 + .2*x3 >= 100;
    > .25*x1 + .15*x2+ .05*x3 >= 150;
    >
    > have uncertainties in x1, x2, and x3 coefficients. I want to know how
    > can I make a robust optimisation model for this LP model?


    This has nothing to do with Python. You might get an answer on the
    scipy mailing list, but you should look for a group of list on numerical
    optimization, or better one specifically on linear programming, which is
    a somewhat separate subfield. Or find a book on 'robust optimization',
    whatever that is.

    tjr
     
    Terry Reedy, Aug 5, 2008
    #2
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