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Publications (2)
In this article, we discuss input modeling and solution techniques for several classes of Chance-Constrained Programs (CCPs). We propose to use a Gaussian Mixture Model (GMM) to fit the data available and to model the randomness. We demonstrate the merits of using a GMM. We consider several scenarios that arise from practical applications and analy...
This paper studies integrated random search algorithms for continuous optimization-via-simulation (COvS) problems. We first tailor the Gaussian process-based search (GPS) algorithm to handle COvS problems. We then analyze the potential sampling issue of the GPS algorithm and propose to construct a desirable Gaussian mixture model (GMM) which is ame...
