@inproceedings{ddf5e35b59b048f4b60e9a9f98cdb180,
title = "Augmented lagrangian constraint handling for CMA-ES — Case of a single linear constraint",
abstract = "We consider the problem of minimizing a function f subject to a single inequality constraint g(x) ≤ 0, in a black-box scenario. We present a covariance matrix adaptation evolution strategy using an adaptive augmented Lagrangian method to handle the constraint. We show that our algorithm is an instance of a general framework that allows to build an adaptive constraint handling algorithm from a general randomized adaptive algorithm for unconstrained optimization. We assess the performance of our algorithm on a set of linearly constrained functions, including convex quadratic and ill-conditioned functions, and observe linear convergence to the optimum.",
author = "Asma Atamna and Anne Auger and Nikolaus Hansen",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2016.; 14th International Conference on Parallel Problem Solving from Nature, PPSN 2016 ; Conference date: 17-09-2016 Through 21-09-2016",
year = "2016",
month = jan,
day = "1",
doi = "10.1007/978-3-319-45823-6\_17",
language = "English",
isbn = "9783319458229",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "181--191",
editor = "Emma Hart and Ben Paechter and Julia Handl and Manuel L{\'o}pez-Ib{\'a}{\~n}ez and Lewis, \{Peter R.\} and Gabriela Ochoa",
booktitle = "Parallel Problem Solving from Nature - 14th International Conference, PPSN 2016, Proceedings",
}