A direct search algorithm for optimization with noisy function evaluations

Conference · Sat Dec 31 00:00:00 EST 1994

OSTI ID:35768

Anderson, E ^[1]; Ferris, M

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1. Univ. of Cambridge, MA (United States)

In this paper we describe a new direct search algorithm, reminiscent of the Nelder-Mead method, and related to a more recent pattern search algorithm proposed by Torczon. We believe that this method has applications in situations in which each function evaluation is noisy, but in which repeated function evaluations at the same point can be used to progressively reduce the error. For example, this will occur if the objective function value is given as a result of a simulation experiment. We investigate the convergence behaviour of the new algorithm for problems in which each function evaluation returns the true value of the function plus a random error drawn from a Normal distribution.

• OSTI ID: 35768
• Report Number(s): CONF-9408161-; TRN: 94:009753-0023
• Resource Relation: Conference: 15. international symposium on mathematical programming, Ann Arbor, MI (United States), 15-19 Aug 1994; Other Information: PBD: 1994; Related Information: Is Part Of Mathematical programming: State of the art 1994; Birge, J.R.; Murty, K.G. [eds.]; PB: 312 p.
• Country of Publication: United States
• Language: English

Related Subjects

99 MATHEMATICS
COMPUTERS
INFORMATION SCIENCE
MANAGEMENT
LAW
MISCELLANEOUS
DATA BASE MANAGEMENT
INFORMATION RETRIEVAL
OPTIMIZATION
ALGORITHMS