scholarly journals A Discrete Stochastic Programming Model to Estimate Optimal Burning Schedules on Rangeland

1987 ◽  
Vol 19 (2) ◽  
pp. 53-60 ◽  
Author(s):  
L. Garoian ◽  
J. R. Conner ◽  
C. J. Scifres
Keyword(s):  
Stochastic Programming ◽  
Programming Model ◽  
Economic Feasibility ◽  
Range Management ◽  
Management Problem ◽  
Treatment Sequence ◽  
Net Returns ◽  
Discrete Stochastic Programming ◽  
Stochastic Programming Model

AbstractMacartney rose is a range management problem on 500,000 acres of rangeland in Texas. Roller chopping followed by burning is an effective method of improving infested rangeland. However, uncertainty associated with implementing effective burns adversely affects economic feasibility of the treatment sequence. Discrete stochastic programming is used to determine optimal burning schedules under uncertainty. Optimal schedules and expected net returns vary with changes in the probability of a successful burn.

scholarly journals A Stochastic Programming Analysis of the Farm Level Implications of Soil Erosion Control

1985 ◽  
Vol 17 (2) ◽  
pp. 147-154 ◽  
Author(s):  
Eduardo Segarra ◽  
Randall A. Kramer ◽  
Daniel B. Taylor
Keyword(s):  
Stochastic Programming ◽  
Soil Loss ◽  
Programming Model ◽  
Farm Level ◽  
Farm Planning ◽  
Net Returns ◽  
Planning Models ◽  
Stochastic Programming Model ◽  
Programming Analysis ◽  
The Impact

AbstractThis paper analyzes the effects of uncertain soil loss in farm planning models. A disaggregated approach was used because of an interest in examining the impact of probabilistic soil loss constraints on farm level decisionmaking. A stochastic programming model was used to consider different levels of probability of soil loss. Traditional methods of analysis are shown to consistently overestimate net returns.

scholarly journals The Effects of Holding Nonfarm Related Financial Assets On Risk-Adjusted Farm Income

1994 ◽  
Vol 26 (2) ◽  
pp. 565-579
Author(s):  
Eustacius N. Betubiza ◽  
David J. Leatham
Keyword(s):  
Stochastic Programming ◽  
Programming Model ◽  
Past Research ◽  
Income Level ◽  
Farm Income ◽  
Financial Assets ◽  
Discrete Stochastic Programming ◽  
Stochastic Programming Model ◽  
Highly Correlated

AbstractA discrete stochastic programming model is formulated to study the gains from diversification when farming operations are augmented with off-farm financial assets that are not highly correlated with returns from farming. We extend past research by considering the dynamics of accumulating these financial assets and the farm's leverage and tenure position. Results show that farmers' income level and stability can be improved by including nonfarm financial assets in their portfolios.

scholarly journals Analysis of a Stochastic Programming Model for Optimal Hydropower System Operation under a Deregulated Electricity Market by Considering Forecasting Uncertainty

Water ◽  
2018 ◽  
Vol 10 (7) ◽  
pp. 885 ◽  
Author(s):  
Bin Xu ◽  
Ping-An Zhong ◽  
Baoyi Du ◽  
Juan Chen ◽  
Weifeng Liu ◽  
...  
Keyword(s):  
Stochastic Programming ◽  
Electricity Market ◽  
Energy Production ◽  
Programming Model ◽  
Optimal Operation ◽  
Spot Price ◽  
Deregulated Electricity Market ◽  
Hydropower System ◽  
Stochastic Programming Model ◽  
Hydropower Operation

In a deregulated electricity market, optimal hydropower operation should be achieved through informed decisions to facilitate the delivery of energy production in forward markets and energy purchase level from other power producers within real-time markets. This study develops a stochastic programming model that considers the influence of uncertain streamflow on hydropower energy production and the effect of variable spot energy prices on the cost of energy purchase (energy shortfall). The proposed model is able to handle uncertainties expressed by both a probability distribution and discretized scenarios. Conflicting decisions are resolved by maximizing the expected value of net revenue, which jointly considers benefit and cost terms under uncertainty. Methodologies are verified using a case study of the Three Gorges cascade hydropower system. The results demonstrate that optimal operation policies are derived based upon systematic evaluations on the benefit and cost terms that are affected by multiple uncertainties. Moreover, near-optimal operation policy under the case of inaccurate spot price forecasts is also analyzed. The results also show that a proper policy for guiding hydropower operation seeks the best compromise between energy production and energy purchase levels, which explores their nonlinear tradeoffs over different time periods.

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