Home

About

Advanced Search

Browse by Discipline

Scientific Societies

E-print Alerts

Add E-prints

E-print Network
FAQHELPSITE MAPCONTACT US


  Advanced Search  

 
An Integer Programming Approach for Linear Programs with Probabilistic Constraints
 

Summary: An Integer Programming Approach for
Linear Programs with Probabilistic Constraints
James Luedtke
Shabbir Ahmed
George Nemhauser
Georgia Institute of Technology
765 Ferst Drive, Atlanta, GA, USA
luedtke@gatech.edu
May 3, 2007
Abstract
Linear programs with joint probabilistic constraints (PCLP) are dif-
ficult to solve because the feasible region is not convex. We consider a
special case of PCLP in which only the right-hand side is random and
this random vector has a finite distribution. We give a mixed-integer
programming formulation for this special case and study the relaxation
corresponding to a single row of the probabilistic constraint. We obtain
two strengthened formulations. As a byproduct of this analysis, we obtain
new results for the previously studied mixing set, subject to an additional
knapsack inequality. We present computational results which indicate
that by using our strengthened formulations, instances that are consider-

  

Source: Ahmed, Shabbir - School of Industrial and Systems Engineering, Georgia Institute of Technology

 

Collections: Engineering