Comparison of two algorithms for solving a two‐stage bilinear stochastic programming problem with quantile criterion |
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Authors: | Andrey Kibzun |
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Affiliation: | Department of Probability Theory, School of Applied Mathematics and Physics, Moscow Aviation Institute, Moscow, Russia |
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Abstract: | The paper is devoted to solving the two‐stage problem of stochastic programming with quantile criterion. It is assumed that the loss function is bilinear in random parameters and strategies, and the random vector has a normal distribution. Two algorithms are suggested to solve the problem, and they are compared. The first algorithm is based on the reduction of the original stochastic problem to a mixed integer linear programming problem. The second algorithm is based on the reduction of the problem to a sequence of convex programming problems. Performance characteristics of both the algorithms are illustrated by an example. A modification of both the algorithms is suggested to reduce the computing time. The new algorithm uses the solution obtained by the second algorithm as a starting point for the first algorithm. Copyright © 2015 John Wiley & Sons, Ltd. |
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Keywords: | stochastic programming two‐stage problem quantile function Value‐at‐Risk criterion confidence method mixed integer linear programming problem convex programming |
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