Role of Dependence in Chance-constrained and Robust Programming

نویسنده

  • Michal Houda
چکیده

The paper deals with two methods of solving optimization programs whereuncertainties occur: stochastic (in particular chance-constrained) programming androbust programming. We review briefly how these two methods deal with uncertaintyand what approximations are commonly used. Furthermore, we are concentrated onapproximations based on sample sets where some type of weak dependence occurs. Wedemonstrate that such kind of dependence does not imply any important malfunction ofoptimization methods used there. Numerical illustration on simple optimizationprogram is given.

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تاریخ انتشار 2009