-

 

 

 




Optimization Online





 

Finding optimal algorithmic parameters using a mesh adaptive direct search

Charles Audet (Charles.Audet***at***gerad.ca)
Dominique Orban (Dominique.Orban***at***polymtl.ca)

Abstract: The objectives of this paper are twofold; we first demonstrate the flexibility of the mesh adaptive direct search (MADS) in identifying locally optimal algorithmic parameters. This is done by devising a general framework for parameter tuning. The framework makes provision for surrogate objectives. Parameters are sought so as to minimize some measure of performance of the algorithm being fine-tuned. This measure is treated as a black-box and may be chosen by the user. Examples are given in the text. The second objective illustrates this framework by specializing it to the identification of locally optimal trust-region parameters in unconstrained optimization. Parameters are identified that minimize, in a certain sense, the computational time or the number of function evaluations required to solve a set of problems from the CUTEr collection. Each function call may take several hours and may not always return a predictable result. A surrogate function, taylored to the experiment at hand, is used to guide the MADS towards a local solution. The parameters thus identified differ from traditionally used values, and are used to solve problems from the CUTEr collection that remained otherwised unsolved in a reasonable time using traditional values.

Keywords: Trust-region methods, unconstrained optimization, mesh adaptive direct search algorithms, black-box optimization, surrrogate functions, parameter estimation

Category 1: Convex and Nonsmooth Optimization (Nonsmooth Optimization )

Category 2: Nonlinear Optimization (Unconstrained Optimization )

Category 3: Nonlinear Optimization

Citation: Cahiers du GERAD G-2004-xx, GERAD, Montreal QC, Canada. December 2004.

Download: [Compressed Postscript][PDF]

Entry Submitted: 12/01/2004
Entry Accepted: 12/02/2004
Entry Last Modified: 12/01/2004

Modify/Update this entry


  Visitors Authors More about us Links
  Subscribe, Unsubscribe
Digest Archive
Search, Browse the Repository

 

Submit
Update
Policies
Coordinator's Board
Classification Scheme
Credits
Give us feedback
Optimization Journals, Sites, Societies
Mathematical Programming Society