Accelerating the regularized decomposition method for two stage stochastic linear problems
Andrzej Ruszczyński , Artur Świętanowski
AbstractPractical improvements of the regularized decomposition algorithm for two stage stochastic problems are presented. They are associated with the primal simplex method for solving subproblems. A penalty formulation of the subproblems is used, which facilitates crash and warm starts, and allows more freedom when creating the model. The computational results are highly encouraging.
|Journal series||European Journal of Operational Research, ISSN 0377-2217|
|Keywords in English||Decomposition, Non-smooth optimization, Stochastic programming|
|Publication indicators||: 2006 = 0.918 (2) - 2007=1.568 (5)|
|Citation count*||93 (2015-04-30)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.