Metode Pengembangan Pendekatan Rata-Rata Sampel Untuk Menyelesaikan Permasalahan Optimisasi Program Stokastik Diskrit

Abstract

This thesis addresses a solution strategy for solving stochastic discrete optimization. Programming problem. The proposed methodology relies on approximation the underlying stochastic program via sampling, and solving the approximate problem via a specialized optimization algorithm. The proposed scheme will produce an optimal solution to the true problem with probability approaching one exponentially fast as the sample size increased