Model Program Stokastik Tahap Ganda dengan Probabilitas Campuran

Abstract

Stochastic programming deal with optimization problems where some of its para- meters is described by uncertainty in variables. The uncertainty means when the value of the parameters involved in objective and constraints function cannot be determined exactly and those random parameters value is replaced by random vari- ables with known probabilities distribution value. The main factors of uncertainty arises within the variables are due to natural characteristic of the variables and type of the problems. This thesis discussed about the model of multistage stochastic programming with mized probabilities where chance-constrained optimization also play an important role in discussion. Results show that the solution of stochastic optimization problems can be obtained by converting it into equivalent determinis- tic model