stochastic programming we characterize analytically (rather than numerically) the optimal decisions that follow from …

-desk seller of malting barley, the Canadian Wheat Board. In this paper, we develop a discrete stochastic programming model to …

stochastic programming we characterize analytically (rather than numerically) the optimal decisions that follow from …

stochastic programming we characterize analytically (rather than numerically) the optimal decisions that follow from …

stochastic programming we characterize analytically (rather than numerically) the optimal decisions that follow from …

Account (NISA) program as an example of a subsidized savings program, a stochastic programming model of income stabilization …

-sequential programming, discrete stochastic programming (DSP) provided more efficient solutions for problems involving embedded risk. There …

possiblilites. We formulate an ALM model for pension funds as a multistage stochastic programming model. Relevant variables such as …

Decision making under uncertainty is a challenge faced by many decision makers. Stochastic programming is a major tool … bond-portfolio management. Computationally however, many models in stochastic programming remain unsolvable because of … are based on decomposing the data. In this paper we propose a new decomposition approach for two-stage stochastic …

possiblilites. We formulate an ALM model for pension funds as a multistage stochastic programming model. Relevant variables such as …