Mesh Adaptive Direct Search Algorithms for Constrained Optimization

By Charles Audet, John E. Dennis Jr.. 2006

1,371 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Numerical Analysis

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Citations in the corpus

Maximum-Likelihood Estimation With a Contracting-Grid Search Algorithm (2010, neutral): “tive-free optimization (DFO) algorithms [5]–[7].”
Joint optimization of oil well placement and controls (2012, methodology): “Examples of these techniques are Hooke–Jeeves direct search (HJDS; [25]), generalized pattern search (GPS; [36], [2]), mesh adaptive direct search (MADS; [3]), and bound optimization by quadratic approximation (BOBYQA; [33]).”
Direct Multisearch for Multiobjective Optimization (2011, methodology): “These two solvers seem clearly the most efficient ones for budgets up to 2500 evaluations, being BIMADS better for more accurate solutions and DMS(n,line) better for less accurate ones.”
Modeling an augmented Lagrangian for improved blackbox constrained optimization (2014, methodology): “In particular, we consider the mesh adaptive direct search (MADS) algorithm (Audet and Dennis, 2006).”
Worst case complexity of direct search (2013, background): “Deviation from smoothness (see [2, 18]) poses several diﬃculties to the derivation of a worst case complexity bound, and such a study will be the subject of a separate paper [9].”
Smoothing and worst-case complexity for direct-search methods in nonsmooth optimization (2013, result): “The lack of a worst case complexity bound for direct search in the non-smooth setting contrasts with the corresponding availability of global convergence results under the assumption of some form of density of the polling directions in the unit sphere (see [35] for the approach using sufficient decr”
A particle swarm pattern search method for bound constrained global optimization (2007, background): “The order in which the points in Pt are evaluated can also differ [4,9].”
Convergence analysis of the direct algorithm (2004, methodology): “We do this using the framework from [1], in which the authors design a sampling algorithm with a very rich set of search directions.”
A derivative-free methodology with local and global search for the constrained joint optimization of well locations and controls (2014, methodology): “We now describe the use of the filter method with MADS (this discussion follows that given by Audet and Dennis [3] for GPS).”
Derivative-free optimization: a review of algorithms and comparison of software implementations (2012, methodology): “MADS handles general constraints by the extreme barrier approach [11], which rejects infeasible trial points from consideration, or by the progressive barrier approach [12], which allows infeasible trial points within a decreasing infeasibility threshold.”
Joint optimization of well placement and control for nonconventional well types (2014, methodology): “Mesh adaptive direct search (MADS) (Audet and Dennis, 2006) is a pattern search algorithm which extends the earlier class of generalized pattern search (GPS) algorithms (e.”
A Survey of Automatic Parameter Tuning Methods for Metaheuristics (2020, methodology): “In that work, bound optimization by quadratic approximation (BOBYQA) [61] was combined with repeated evaluation, and mesh adaptive direct search (MADS) [62] was combined with both repeated evaluation and F -Race to solve parameter tuning problems.”