conveks is a framework for formulating and solving large-scale nonlinear constrained optimization problems in an efficient and portable manner. The default algorithm provided by conveks is the method of moving asymptotes (MMA)1, implemented using PETSc.
conveks is Copyright (c) 2018, E. Kuci, C. Geuzaine and P. Duysinx, University of Liège.
conveks is distributed as part of the ONELAB software bundle to solve large scale finite element shape or topology optimization problems, using both direct and adjoint formulations2. To test conveks:
This assumes that you have a working Python installation on your computer, including the NumPy package.
A Software Development Kit (SDK) is also available for integrating conveks with your own C, C++, Python or Julia code.
Download the conveks SDK for Windows, Linux or macOS.
The conveks source code is currently not publicly available: contact the authors for further information.
conveks development was funded in part by the Walloon Region under WBGreen grant No 1217703 (FEDO) and the the Belgian Science Policy under grant IAP P7/02.