Abstract: Water resource policy formulation proves complicated because water management systems generally contain numerous sources of stochastic uncertainty. Simulation-Optimization (SO) methods, which incorporate system uncertainties using probability distributions, have been used for optimization in environmental planning. In this study, it will be shown that, in addition to function optimization, SO can be extended to formulate multiple policy alternatives meeting required system criteria-an approach referred to as Modelling to Generate Alternatives (MGA). Unfortunately, while SO holds considerable potential for application to a wide range of stochastic problems, its solution search times are, themselves, stochastic and vary considerably from one implementation to the next. Consequently, additional concurrent techniques will be presented to significantly reduce SO search times. The efficacy of this MGA approach for policy formulation is illustrated using a specific water resource management case study. Of significance is that, since SO techniques can be adapted to many disparate problems containing significant sources of uncertainty, the practicality of this approach can be extended to many other policy formulation applications, which contain stochastic system components.