Kleinert T, Schmidt M, Plein F, Labbé M (2020)
Publication Language: English
Publication Status: Accepted
Publication Type: Journal article, Original article
Future Publication Type: Journal article
Publication year: 2020
Book Volume: 68
Pages Range: 1625-1931
Article Number: C2
Journal Issue: 6
URI: https://pubsonline.informs.org/doi/10.1287/opre.2019.1944
One of the most frequently used approaches to solve linear bilevel optimization problems consists in replacing the lower-level problem with its Karush-Kuhn-Tucker (KKT) conditions and by reformulating the KKT complementarity conditions using techniques from mixed-integer linear optimization. The latter step requires to determine some big-M constant in order to bound the lower level's dual feasible set such that no bilevel optimal solution is cut off. In practice, heuristics are often used to find a big-M although it is known that these approaches may fail. In this paper, we consider the hardness of two proxies for the above mentioned concept of a bilevel-correct big-M. First, we prove that verifying that a given big-M does not cut off any feasible vertex of the lower level's dual polyhedron cannot be done in polynomial time unless P=NP. Second, we show that verifying that a given big-M does not cut off any optimal point of the lower level's dual problem is as hard as solving the original bilevel problem.
APA:
Kleinert, T., Schmidt, M., Plein, F., & Labbé, M. (2020). There's No Free Lunch: On the Hardness of Choosing a Correct Big-M in Bilevel Optimization. Operations Research, 68(6), 1625-1931. https://doi.org/10.1287/opre.2019.1944
MLA:
Kleinert, Thomas, et al. "There's No Free Lunch: On the Hardness of Choosing a Correct Big-M in Bilevel Optimization." Operations Research 68.6 (2020): 1625-1931.
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