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Revisiting Benders Decomposition

Boris Detienne 1, 2 Ruslan Sadykov 1, 2 Halil Şen 1, 2 Francois Vanderbeck 1, 2 
1 Realopt - Reformulations based algorithms for Combinatorial Optimization
LaBRI - Laboratoire Bordelais de Recherche en Informatique, IMB - Institut de Mathématiques de Bordeaux, Inria Bordeaux - Sud-Ouest
Abstract : Benders decomposition entails a two-stage optimization approach to a mixed integer program: first-stage decision variables are optimized using a polyhedral approximation of the problem's projection; then a separation problem expressed in the second-stage variables is solved to check if the current first-stage solution is feasible; otherwise, it produces a violated inequality. Such cutting-plane algorithm can suffer severe drawbacks regarding its convergence rate. We review the battery of approaches that have been proposed in the literature to address these drawbacks and to speed-up the algorithm. Our contribution consists in proposing a unified framework to explain these techniques, showing that in several cases, different proposals of the literature boil down to the same key ideas. We complete this review with a numerical study of implementation options for Benders algorithmic features and enhancements.
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Conference papers
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Contributor : François Vanderbeck Connect in order to contact the contributor
Submitted on : Tuesday, February 14, 2017 - 12:00:12 PM
Last modification on : Saturday, June 25, 2022 - 10:37:18 AM


  • HAL Id : hal-01467283, version 1



Boris Detienne, Ruslan Sadykov, Halil Şen, Francois Vanderbeck. Revisiting Benders Decomposition. Symposium Combinatorial Optimization and Applications, Feb 2017, Edinburgh, United Kingdom. ⟨hal-01467283⟩



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