Approximating the Expected Values for Combinatorial Optimization Problems over Stochastic Points
نویسندگان
چکیده
We consider the stochastic graph model where the location of each vertex is a random point in a given metric space. We study the problems of computing the expected lengths of the minimum spanning tree, the minimum perfect matching and the minimum cycle cover on such a stochastic graph and obtain an FPRAS (Fully Polynomial Randomized Approximation Scheme) for each of these problems. Our result for stochastic minimum spanning trees improves upon the previously known constant factor approximation algorithm. Our results for the stochastic minimum perfect matching and the stochastic minimum cycle cover are the first known algorithms to the best of our knowledge.
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