Benders' decomposition

From Wikipedia, the free encyclopedia
Jump to: navigation, search

Benders' decomposition (or Benders's decomposition) is a technique in mathematical programming that allows the solution of very large linear programming problems that have a special block structure. This block structure often occurs in applications such as stochastic programming. The technique is named after Jacques F. Benders.

As it progresses towards a solution, Benders' decomposition adds new constraints, so the approach is called "row generation". In contrast, Dantzig–Wolfe decomposition uses "column generation".

See also[edit]

  • FortSP solver uses Benders' decomposition for solving stochastic programming problems