Study Of Some Algorithms For Stochastic Programs And Its Applications

This paper introduces the development of stochastic programming systematicallywhile summarizing and analyzing the fruits on this field during the past. Based on thestudy of some researchers, we study several algorithms and its applications, especiallyon how to solve stochastic programming with Interior-point method. The whole papercontains four chapters, and it is arranged as follows.In the first chapter, we summarily introduce the development and the currentresearch situations as well as the classification about stochastic programming.In the second chapter, we show a Log-Barrier method with Benders decompositionfor solving two-stage linear stochastic programming, and then we solve the problemwith kkt condition of the sub-problem. The method is not only shown that with finiterealization of random variable to be globally convergent but shown to bepolynomial-time complexity.In the third chapter, we present another Log-Barrier method, but withDantzig-Wolfe decomposition and Lagrangian Dual method for solving two-stagenonlinear stochastic programming. It is in the same convergence and polynomial-timecomplexity with the second method.During the last chapter, with stochastic programming theory, and based onproduction and supply plan, we give a multi-stage stochastic programming model.