We describe an algorithmic framework generalizing the well-known framework originally introduced by Benders. We apply this framework to several classes of optimization problems that fall under the broad umbrella of multilevel/multistage mixed integer linear optimization problems. The development of the abstract framework and its application to this broad class of problems provides new insights and new ways of interpreting the core ideas, especially those related to duality and the value function of an optimization problem.
COR@L Laboratory Technical Report 20T-004, Lehigh University http://coral.ie.lehigh.edu/~ted/files/papers/MultilevelBenders20.pdf
View A Framework for Generalized Benders’ Decomposition and Its Application to Multilevel Optimization