A method employing decomposition techniques and Monte Carlo sampling (importance sampling) to solve stochastic linear programs is described and applied to capacity expansion planning problems of electric utilities. We consider uncertain availability of generators and transmission lines and uncertain demand. Numerical results are presented.

We describe an extension of the pseudo maximum likelihood (PML) estimation method developed by Skinner (1989) to multistage strati ̄ed cluster sampling designs, including ̄nite population and unequal probability sampling. We conduct simulation studies to evaluate the performance of the proposed estimator. The estimator is also compared to the general estimating equation (GEE) method for linear r...