OPTLAB

Large-Scale Nonlinear Constrained Optimization Library

OPTLAB (OPTimization LABoratory) is a framework for formulating and solving large-scale, nonlinear constrained optimization problems in an efficient and portable manner. The default algorithm provided by OPTLAB is the method of moving asymptotes (MMA)1, implemented for both shared and distributed (MPI) memory architectures using PETSc.

OPTLAB is Copyright (c) 2018, E. Kuci, C. Geuzaine and P. Duysinx, University of Liège.

Quick start

OPTLAB is distributed as part of the ONELAB bundle to solve large scale finite element shape or topology optimization problems2. To test OPTLAB:

  1. Dowload the ONELAB software bundle
  2. Launch the app
  3. Open tutorials/optlab/shape.py
  4. Press Run

This assumes that you have a working Python installation on your computer, including the numpy package.

OPTLAB Software Development Kit

A Software Development Kit (SDK) is also available for integrating OPTLAB with your own C, C++, Python or Julia code.

Download the SDK for Windows 64-bit, Windows 32-bit, Linux 64-bit, Linux 32-bit or MacOS.

References

  1. K. Svanberg. The method of moving asymptotes - a new method for structural optimization. International journal for numerical methods in engineering, 24 (2):359–373, 1987.
  2. E. Kuci, F. Henrotte, P. Duysinx, and C. Geuzaine. Design sensitivity analysis for shape optimization based on the Lie derivative. Computer Methods in Applied Mechanics and Engineering 317 (2017), pp. 702 –722.

Sponsors

OPTLAB 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.