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Many real world problems in optimization are too complex to be given tractable mathematical formulations. Multiple nonlinearities, combinatorial relationships and uncertainties often render challenging practical problems inaccessible to modeling except by resorting to simulation -an outcome that poses grave difficulties for classical optimization methods. In such situations, recourse is commonly made to itemizing a series of scenarios in the hope that at least one will give an acceptable solution. Consequently, a long standing goal in both the optimization and simulation communities has been to create a way to guide a series of simulations to produce high quality solutions, in the absence of tractable mathematical structures.
Glover et al. (Fri,) studied this question.
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