TY - JOUR
T1 - Convex envelopes for ray-concave functions
AU - Barrera, Javiera
AU - Moreno, Eduardo
AU - Muñoz, Gonzalo
N1 - Funding Information:
The research leading to these results received funding from grants ANID/CONICYT-Fondecyt Regular 1200809 (J.B., E.M.), MathAmsud 19-MATH-03 (J.B.) and ANID/CONICYT-Fondecyt Iniciación 11190515 (G.M.). We would also like to thank Felipe Serrano for helpful discussions and to the anonymous reviewer for their valuable feedback.
Funding Information:
The research leading to these results received funding from grants ANID/CONICYT-Fondecyt Regular 1200809 (J.B., E.M.), MathAmsud 19-MATH-03 (J.B.) and ANID/CONICYT-Fondecyt Iniciación 11190515 (G.M.). We would also like to thank Felipe Serrano for helpful discussions and to the anonymous reviewer for their valuable feedback.
Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2022/11
Y1 - 2022/11
N2 - Convexification based on convex envelopes is ubiquitous in the non-linear optimization literature. Thanks to considerable efforts of the optimization community for decades, we are able to compute the convex envelopes of a considerable number of functions that appear in practice, and thus obtain tight and tractable approximations to challenging problems. We contribute to this line of work by considering a family of functions that, to the best of our knowledge, has not been considered before in the literature. We call this family ray-concave functions. We show sufficient conditions that allow us to easily compute closed-form expressions for the convex envelope of ray-concave functions over arbitrary polytopes. With these tools, we are able to provide new perspectives to previously known convex envelopes and derive a previously unknown convex envelope for a function that arises in probability contexts.
AB - Convexification based on convex envelopes is ubiquitous in the non-linear optimization literature. Thanks to considerable efforts of the optimization community for decades, we are able to compute the convex envelopes of a considerable number of functions that appear in practice, and thus obtain tight and tractable approximations to challenging problems. We contribute to this line of work by considering a family of functions that, to the best of our knowledge, has not been considered before in the literature. We call this family ray-concave functions. We show sufficient conditions that allow us to easily compute closed-form expressions for the convex envelope of ray-concave functions over arbitrary polytopes. With these tools, we are able to provide new perspectives to previously known convex envelopes and derive a previously unknown convex envelope for a function that arises in probability contexts.
KW - Convex envelopes
KW - Convex optimization
KW - Nonlinear programming
UR - http://www.scopus.com/inward/record.url?scp=85124340537&partnerID=8YFLogxK
U2 - 10.1007/s11590-022-01852-2
DO - 10.1007/s11590-022-01852-2
M3 - Article
AN - SCOPUS:85124340537
VL - 16
SP - 2221
EP - 2240
JO - Optimization Letters
JF - Optimization Letters
SN - 1862-4472
IS - 8
ER -