I'll be giving the invited talk "Unifying nonlinearly constrained nonconvex optimization" at JuMP-dev 2024 in July. Thank you for your invitation and see you on July 20th! Abstract: Derivative-based iterative methods for nonlinearly constrained nonconvex optimization usually share common algorithmic components, such as strategies for computing a descent direction and mechanisms that promote global convergence. Based on this observation, we introduce an abstract framework with four common ingredients that describes most derivative-based iterative methods and unifies their workflows. We then present Uno, a modular C++ solver that implements our abstract framework and allows the automatic generation of various strategy combinations with no programming effort from the user. Uno is meant to (1) organize mathematical optimization strategies into a coherent hierarchy; (2) offer a wide range of efficient and robust methods that can be compared for a given instance; (3) reduce the cost of development and maintenance of multiple optimization solvers; and (4) enable researchers to experiment with novel optimization strategies while leveraging established subproblem solvers and interfaces to modeling languages. We demonstrate that Uno is highly competitive against state-of-the-art solvers such as filterSQP, IPOPT, SNOPT, MINOS, LANCELOT, LOQO and CONOPT on a set of 429 problems from the CUTEst collection. Uno is available as open-source software under the MIT license at https://lnkd.in/ehGBGYXk. #optimization #julia #jump #jumpdev #unosolver
Tickets for JuMP-dev 2024 (19-21 July, Montréal, Canada) are now on sale! We have 29 great talks across two days, plus an unstructured hackathon to hack on new features, discuss plans for the future, and hear feedback from users. For more details, go to https://lnkd.in/eE525Zdd
