-

 

 

 




Optimization Online





 

Inverse Stochastic Linear Programming

Gorkem Saka(gorkems***at***ie.pitt.edu)
Andrew J. Schaefer(schaefer***at***ie.pitt.edu)
Lewis Ntaimo(ntaimo***at***tamu.edu)

Abstract: Inverse optimization perturbs objective function to make an initial feasible solution optimal with respect to perturbed objective function while minimizing cost of perturbation. We extend inverse optimization to two-stage stochastic linear programs. Since the resulting model grows with number of scenarios, we present two decomposition approaches for solving these problems.

Keywords: Inverse Optimization, Stochastic Programming,Decomposition Algorithms

Category 1: Stochastic Programming

Citation: Unpublished: 07-1, University of Pittsburgh, Pittsburgh PA 15261, January 2007.

Download: [PDF]

Entry Submitted: 01/05/2007
Entry Accepted: 01/05/2007
Entry Last Modified: 01/05/2007

Modify/Update this entry


  Visitors Authors More about us Links
  Subscribe, Unsubscribe
Digest Archive
Search, Browse the Repository

 

Submit
Update
Policies
Coordinator's Board
Classification Scheme
Credits
Give us feedback
Optimization Journals, Sites, Societies
Mathematical Programming Society