A branch-and-cut algorithm for mixed integer bilevel linear optimization problems and its implementation

  • In this paper, we describe a comprehensive algorithmic framework for solving mixed integer bilevel linear optimization problems (MIBLPs) using a generalized branch-and-cut approach. The framework presented merges features from existing algorithms (for both traditional mixed integer linear optimization and MIBLPs) with new techniques to produce a flexible and robust framework capable of solving a wide range of bilevel optimization problems. The framework has been fully implemented in the open-source solver MibS. The paper describes the algorithmic options offered by MibS and presents computational results evaluating the effectiveness of the various options for the solution of a number of classes of bilevel optimization problems from the literature.

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Metadaten
Author:Sahar Tahernejad, Ted K. Ralphs, Scott T. DeNegre
DOI:https://doi.org/10.1007/s12532-020-00183-6
ISSN:1867-2949
Parent Title (English):Mathematical Programming Computation
Publisher:Springer Science and Business Media LLC
Document Type:Article
Language:English
Year of Completion:2020
Tag:Software; Theoretical Computer Science
Volume:12
Issue:4
Page Number:40
First Page:529
Last Page:568
Mathematical Programming Computation :MPC 2020 - Issue 4
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