Benders Decomposition
Benders Decomposition is a decomposition algorithm in mathematical optimization that separates a complex problem into a master problem and one or more subproblems, distinguishing itself by iteratively generating Benders cuts—valid inequalities derived from dual information of the subproblems—to refine the master problem toward global optimality in large-scale, stochastic, or integer programming contexts.
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Benders' Decomposition
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Mixed-integer nonlinear optimization
Pietro Belotti, Christian Kirches, Sven Leyffer et al. · Acta Numerica · 2013 · 688 citations
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Illinois Institute of Technology, United States
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Illinois Institute of Technology
Chicago, United States
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Tsinghua University
Beijing, China
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104 publications
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University of Tehran
Tehran, Iran
20 h-index
42 publications
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Carnegie Mellon University
Pittsburgh, United States
19 h-index
31 publications
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HEC Montréal
Montreal, Canada
19 h-index
38 publications
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University of Toronto
Toronto, Canada
18 h-index
38 publications
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Polytechnique Montréal
Montreal, Canada
17 h-index
31 publications
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Shanghai Jiao Tong University
Shanghai, China
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31 publications
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