Approximation in Linear Stochastic Programming Using L-Shaped Method

Approximation algorithm is inveterate solution method in stochastic programming because the problem of stochastic programming is very difficult solved. Therefore, most research in this case is focussed for designing the solution method which approximate optimal solution. This research tells a strategy to finish the problem of stochastic linear programming by approximation with L-Shaped method. This thesis gets result of approximation for stochastic model by fulfilling all linear constraint where optimal solution reached depend on selected partition.