NOMAD - A blackbox optimization software

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NOMAD is a C++ implementation of the Mesh Adaptive Direct Search algorithm (MADS), designed for difficult blackbox optimization problems. These problems occur when the functions defining the objective and constraints are the result of costly computer simulations.

Features

  • Blackbox, nonsmooth optimization
  • Nonlinear constrained optimization
  • Single or biobjective problems
  • Derivative-free optimization
  • Continuous, integer & categorical variables
  • MADS algorithm
  • Matlab and Python interfaces
  • Parallelism with MPI
  • LGPL licence
  • Designed for real problems

Support

Nomad releases

Date Version Functionality
2018-07
2018-06
2015-08
2015-03
2014-09
3.9.1
3.9.0
3.8
3.7
3.6
Minor fixes
Nelder-Mead search
Granular variables, surrogate library, robust optimization, Python interface
Anisotropic scaling, shared object libraries, performance improvements
Matlab interface, evaluations in blocks

Developpers

Industrial partners and funding agencies

How to cite NOMAD [bibtex]

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C. Audet, S. Le Digabel, C. Tribes and V. Rochon Montplaisir. The NOMAD project. Software available at https://www.gerad.ca/nomad.

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S. Le Digabel. Algorithm 909: NOMAD: Nonlinear Optimization with the MADS algorithm. ACM Transactions on Mathematical Software, 37(4):44:1–44:15, 2011.

References for the theory and algorithms [bibtex]

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C. Audet and J. E. Dennis, Jr. Mesh adaptive direct search algorithms for constrained optimization. SIAM Journal on Optimization, 17(1):188–217, 2006.

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C. Audet and W. Hare. Derivative-Free and Blackbox Optimization. Springer Series in Operations Research and Financial Engineering, Springer International Publishing, 302 pages, December 2017.

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