Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4959948 | European Journal of Operational Research | 2017 | 11 Pages |
Abstract
We consider convex optimization problems formulated using dynamic programing equations. Such problems can be solved using the Dual Dynamic Programing algorithm combined with the Level 1 cut selection strategy or the Territory algorithm to select the most relevant Benders cuts. We propose a limited memory variant of Level 1 and show the convergence of DDP combined with the Territory algorithm, Level 1 or its variant for nonlinear optimization problems. In the special case of linear programs, we show convergence in a finite number of iterations. Numerical simulations illustrate the interest of our variant and show that it can be much quicker than a simplex algorithm on some large instances of portfolio selection and inventory problems.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Vincent Guigues,