posted on 2025-05-09, 14:26authored byNatashia Boland, Santanu S. Dey, Thomas Kalinowski, Marco Molinaro, Fabian Rigterink
We investigate how well the graph of a bilinear function b:[0,1]n → ℝ can be approximated by its McCormick relaxation. In particular, we are interested in the smallest number c such that the difference between the concave upper bounding and convex lower bounding functions obtained from the McCormick relaxation approach is at most c times the difference between the concave and convex envelopes. Answering a question of Luedtke, Namazifar and Linderoth, we show that this factor c cannot be bounded by a constant independent of n. More precisely, we show that for a random bilinear function b we have asymptotically almost surely c ⩾ √n/4. On the other hand, we prove that c ⩽ 600√n, which improves the linear upper bound proved by Luedtke, Namazifar and Linderoth. In addition, we present an alternative proof for a result of Misener, Smadbeck and Floudas characterizing functions b for which the McCormick relaxation is equal to the convex hull.
Funding
ARC
LP110200524
History
Journal title
Mathematical Programming
Volume
162
Issue
1-2
Pagination
523-535
Publisher
Springer
Language
en, English
College/Research Centre
Faculty of Science
School
School of Mathematical and Physical Sciences
Rights statement
This is a post-peer-review, pre-copyedit version of an article published in Mathematical Programming. The final authenticated version is available online at: http://dx.doi.org/ 10.1007/s10107-016-1031-5.