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Geometric programming is
closely related to [[convex optimization]]: any GP can be made convex by means of a change of variables.<ref name="tutorial"/> GPs have numerous applications, including component sizing in [[Integrated circuit|IC]] design,<ref>M. Hershenson, S. Boyd, and T. Lee. ''[https://web.stanford.edu/~boyd/papers/opamp.html Optimal Design of a CMOS Op-amp via Geometric Programming].'' Retrieved 8 January 2019.</ref><ref> S. Boyd, S. J. Kim, D. Patil, and M. Horowitz. ''[https://web.stanford.edu/~boyd/papers/gp_digital_ckt.html Digital Circuit Optimization via Geometric Programming].'' Retrieved 20 October 2019.</ref> aircraft design,<ref>W. Hoburg and P. Abbeel. ''[https://people.eecs.berkeley.edu/~pabbeel/papers/2014-AIAA-GP-aircraft-design.pdf Geometric programming for aircraft design optimization].'' AIAA Journal 52.11 (2014): 2414-2426.</ref> [[maximum likelihood estimation]] for [[logistic regression]] in [[statistics]], and parameter tuning of positive [[Linear dynamical system|linear systems]] in [[control theory]].<ref>{{Cite journal|last=Ogura|first=Masaki|last2=Kishida|first2=Masako|last3=Lam|first3=James|date=2020|title=Geometric Programming for Optimal Positive Linear Systems|url=https://ieeexplore.ieee.org/document/8936427/|journal=IEEE Transactions on Automatic Control|volume=65|issue=11|pages=4648–4663|doi=10.1109/TAC.2019.2960697|issn=0018-9286|arxiv=1904.12976}}</ref>
==Convex form==
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