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András Prékopa (September 11, 1929 – September 18, 2016) was a Hungarian mathematician, a member of the Hungarian Academy of Sciences. He was one of the pioneers of stochastic programming and has been a major contributor to its literature. He amended one of the three basic model types of the discipline, chance-constrained programming, by taking into account stochastic dependence among the random variables involved. One of his main results in the area concerns the convexity theory of probabilistically constrained stochastic optimization problems. He introduced the concept of logarithmic concave measures and provided several fundamental theorems on logconcavity, which supplied proofs for the convexity of a wide class of probabilistically constrained stochastic programming problems. These results had impact far beyond the area of mathematical programming, as they found applications in physics, economics, statistics, convex geometry and other fields. (Source: DBPedia)
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