Investigation of Aggregation Problem in Two-Stage Stochastic Linear Programming

Abstract

The paper focuses on a two-stage stochastic linear programming problem when second stage variables depend on a random parameter with a normal (Gaussaian) distribution. Modified L-shaped algorithm using the optimization software CPLEX was applied to solve this problem. The aggregation scenario to reduce the number of iterations of the optimization process, the amount of resources to be used and the time required to produce an optimal solution have been analyzed in the paper. The efficiency of aggregation method was tested using statistical simulation method.