Decomposition methods in stochastic programming
AbstractStochastic programming problems have very large dimension and characteristic structures which are tractable by decomposition. We review basic ideas of cutting plane methods, augmented Lagrangian and splitting methods, and stochastic decomposition methods for convex polyhedral multi-stage stochastic programming problems.
|Journal series||Mathematical Programming, ISSN 0025-5610, 1436-4646|
|Keywords in English||Calculus of Variations and Optimal Control, Combinatorics, Decomposition, Dual methods, Mathematical and Computational Physics, Mathematical Methods in Physics, Mathematics of Computing, numerical analysis, optimization, Primal methods, Stochastic methods, Stochastic programming|
|Citation count*||170 (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.