Author jbrea
Popularity
3 Stars
Updated Last
1 Year Ago
Started In
August 2019

Mesh Adaptive Direct Search (MADS)

This is a pure Julia implementation of (Robust)LtMADS and (Robust)OrthoMADS for blackbox optimization. See NOMAD.jl for a julia wrapper of NOMAD.

Installation

Type `]` in the Julia REPL to enter the package REPL, then

`add https://github.com/jbrea/MeshAdaptiveDirectSearch.jl`

and backspace or ^C to leave it again.

Usage

```using MeshAdaptiveDirectSearch

f(x) = (1 - exp(-sum(abs2, x))) * max(sum(abs2, x .- [30, 40]), sum(abs2, x .+ [30, 40]))
noisyf(x) = f(x) + .1 * randn()

minimize(LtMADS(2), f, [-2.1, 1.7], lowerbound = [-10, -10], upperbound = [10, 10])
minimize(LtMADS(2), f, [-2.1, 1.7], lowerbound = [-10, -10], upperbound = [10, 10], constraints = [x -> sum(x) < .5])
minimize(OrthoMADS(2), f, [-2.1, 1.7], lowerbound = [-10, -10], upperbound = [10, 10])
minimize(RobustLtMADS(2), noisyf, [-2.1, 1.7], lowerbound = [-10, -10], upperbound = [10, 10])
minimize(RobustOrthoMADS(2), noisyf, [-2.1, 1.7], lowerbound = [-10, -10], upperbound = [10, 10])```

To get help, press `?` in the Julia REPL, then e.g. `minimize`.

References

Audet, Charles and Dennis, J. E., "Mesh Adaptive Direct Search Algorithms for Constrained Optimization", 2006, doi

Abramson, Mark A. and Audet, Charles and Dennis, J. E. and Le Digabel, Sébastien, "OrthoMADS: A Deterministic MADS Instance with Orthogonal Directions", 2009, doi.

Audet, Charles and Ianni, Andrea and Le Digabel, Sébastien and Tribes, Christophe, "Reducing the Number of Function Evaluations in Mesh Adaptive Direct Search Algorithms", 2014, doi

Audet, Charles and Ihaddadene, Amina and Le Digabel, Sébastien and Tribes, Christophe, "Robust optimization of noisy blackbox problems using the Mesh Adaptive Direct Search algorithm", 2018, doi

Used By Packages

No packages found.