hedging in the presence of demand uncertainty. In this situation, we find that the integrated model can result in better …In this paper, we present a multi-stage stochastic programming model that integrates financial hedging decisions into … particular, we show that, in the illustrative example, the exchange-rate uncertainty cannot be completely eliminated by financial …

resource allocation is dealing with the uncertainty in the system, particularly with respect to reservoir inflow. Stochastic … non-linear programming is applied to water resource allocation to accommodate this uncertainty across the time periods of … the planning horizon. A large range of solutions is produced representing the distributions of uncertainty in reservoir …

-diversion planning under uncertainty. Compared with other conventional methods, DITRP improves upon them by addressing system …

uncertainty into the planning process. …

case of planning GHG-emission mitigation, demonstrating that IFSP is applicable to reflecting complexities of multi-uncertainty …

case study. Different uncertainty parameters were taken into consideration by a disaggregate analysis of a bottom-up energy …

the time horizon where aspects of real options theory are considered within the planning process. Hedging in the recourse … values and preferences, and exploring trade-offs between competing objectives in the face of underlying uncertainty. As a … aspects of flexibility to demand growth uncertainty into each future expansion alternative by introducing stochastic …

uncertainty. Uncertainty in the energy market prices is the main cause of high volatility of profits achieved by power producers …. The volatile and intermittent nature of wind energy represents another source of uncertainty. Hence, each uncertain …

Increased uncertainty is one of the characteristics of product recovery networks. In particular the strategic design of …