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Conference Papers Year : 2017

Revisiting Benders Decomposition

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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Dates and versions

hal-01467283 , version 1 (14-02-2017)

Identifiers

  • HAL Id : hal-01467283 , version 1

Cite

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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CNRS INRIA INRIA2
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