A NEW PARTIAL SAMPLE AVERAGE APPROXIMATION METHOD FOR CHANCE CONSTRAINED PROBLEM
Abstract: In this paper, we present a new scheme of a sampling method to solve chance constrained programs. First of all, a modified sample average approximation, namely Partial Sample Average Approximation (PSAA) is presented. The main advantage of our approach is that the PSAA problem has only continuous variables whilst the standard sample average approximation (SAA) contains binary variables. Although our approach generates new chance constraints, we show that such constraints are easily tractable. Moreover, it is shown that PSAA has the same convergence properties as SAA. Finally, numerical experiments are conducted to compare the proposed approximation to SAA in order to show the strength of our new sample method.
Keywords: Stochastic programming · Chance constraints, Sampling approximation
Category 1: Stochastic Programming
Citation: Working Paper N° 1574. University of Paris Sud,LRI 10/2014.
Entry Submitted: 11/03/2014
Modify/Update this entry
|Visitors||Authors||More about us||Links|
Search, Browse the Repository
Give us feedback
|Optimization Journals, Sites, Societies|