Stochastic Adaptive Search Methods: Theory and Implementation

Random search algorithms are very useful for simulation optimization, because they are relatively easy to implement and typically find a “good” solution quickly. One drawback is that strong convergence results to a global optimum require strong assumptions on the structure of the problem.

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