scholarly journals An alternating method for stochastic linear programming with simple recourse

1986 ◽  
pp. 183-190 ◽  
Author(s):  
Liqun Qi
Keyword(s):  
Linear Programming ◽  
Stochastic Linear Programming ◽  
Alternating Method ◽  
Simple Recourse

Abstract: Short-Term Financial Planning under Uncertainty

1977 ◽  
Vol 12 (4) ◽  
pp. 665-665
Author(s):  
J. G. Kallberg ◽  
R. W. White ◽  
W. T. Ziemba
Keyword(s):  
Linear Programming ◽  
Financial Planning ◽  
Programming Model ◽  
Planning Horizon ◽  
Planning Under Uncertainty ◽  
Stochastic Linear Programming ◽  
Short Term ◽  
Simple Recourse ◽  
The Cost ◽  
Novel Algorithm

The essence of short-term financial planning is to determine an asset and liability mix that minimizes the cost of financing the firm's cash surpluses and deficits over the planning horizon. Seasonal and other effects cause uncertainty in forecasted cash requirements, liquidation, and termination costs. We develop a stochastic linear programming model that is computationally feasible for a firm's financial planning over several periods with all three types of uncertainty when there is a rich structure over the set of possible asset choices. The models' solution is facilitated using a recent novel algorithm for finitely distributed simple recourse SLPR problems developed by Wets and coded by Collins, Kallberg and Kusy. The algorithm uses a “working basis” that has the same dimension as the corresponding (approximate) “mean” linear program.

scholarly journals Planning of Electric Power Systems Considering Virtual Power Plants with Dispatchable Loads Included: An Inexact Two-Stage Stochastic Linear Programming Model

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Changyu Zhou ◽  
Guohe Huang ◽  
Jiapei Chen
Keyword(s):  
Linear Programming ◽  
Power System ◽  
Electric Power ◽  
Power Supply ◽  
Power Plants ◽  
Electricity Demand ◽  
Virtual Power ◽  
Stochastic Linear Programming ◽  
Two Stage ◽  
Virtual Power Plants

In this study, an inexact two-stage stochastic linear programming (ITSLP) method is proposed for supporting sustainable management of electric power system under uncertainties. Methods of interval-parameter programming and two-stage stochastic programming were incorporated to tackle uncertainties expressed as interval values and probability distributions. The dispatchable loads are integrated into the framework of the virtual power plants, and the support vector regression technique is applied to the prediction of electricity demand. For demonstrating the effectiveness of the developed approach, ITSLP is applied to a case study of a typical planning problem of power system considering virtual power plants. The results indicate that reasonable solutions for virtual power plant management practice have been generated, which can provide strategies in mitigating pollutant emissions, reducing system costs, and improving the reliability of power supply. ITSLP is more reliable for the risk-aversive planners in handling high-variability conditions by considering peak-electricity demand and the associated recourse costs attributed to the stochastic event. The solutions will help decision makers generate alternatives in the event of the insufficient power supply and offer insight into the tradeoffs between economic and environmental objectives.

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