Pattern Search Optimization with a Treed Gaussian Process Oracle
نویسندگان
چکیده
This work combines pattern search optimization with a statistical emulator based on Treed Gaussian Processes (TGP) to create a new hybrid algorithm. The goal is to use the global probabilistic view provided by TGP to inform the local pattern search and form a more intelligent optimization algorithm. We also propose ways in which the emulator can be used to gain information about the objective function, inform the algorithm stopping rules and provide a probabilistic analysis of the type of convergence. We present the algorithm, a framework for statistically informed optimization, and illustrate the work with numerical results.
منابع مشابه
Bayesian Guided Pattern Search for Robust Local Optimization
Optimization for complex systems in engineering often involves the use of expensive computer simulation. By combining statistical emulation using treed Gaussian processes with pattern search optimization, we are able to perform robust local optimization more efficiently and effectively than using either method alone. Our approach is based on the augmentation of local search patterns with locati...
متن کاملThe mesh adaptive direct search algorithm with treed Gaussian process surrogates ∗
This work introduces the use of the treed Gaussian process (TGP) as a surrogate model within the mesh adaptive direct search (MADS) framework for constrained blackbox optimization. It extends the surrogate management framework (SMF) to nonsmooth optimization under general constraints. MADS uses TGP in two ways: one, as a surrogate for blackbox evaluations; and two, to evaluate statistical crite...
متن کاملDesigning and analyzing a circuit device experiment using treed Gaussian processes
The development of circuit devices can involve both physical and computer simulation experiments. Here, we discuss statistical solutions for both design of the physical experiment and optimization for the calibration of the computer model. In both cases, we can view the problem as one of optimization, and we rely upon treed Gaussian processes to model the data and guide our design choices.
متن کاملEnhancing Parallel Pattern Search Optimization with a Gaussian Process Oracle
We consider a derivative-free method from the pattern search class of algorithms for the solution of simulationbased optimization problems. Because simulations often require significant computational time and resources, we are striving to reduce the number of runs needed by the optimization method. Moreover, since pattern searches are local methods, we are investigating ways of introducing robu...
متن کاملCategorical Inputs, Sensitivity Analysis, Optimization and Importance Tempering with tgp Version 2, an R Package for Treed Gaussian Process Models
This document describes the new features in version 2.x of the tgp package for R, implementing treed Gaussian process (GP) models. The topics covered include methods for dealing with categorical inputs and excluding inputs from the tree or GP part of the model; fully Bayesian sensitivity analysis for inputs/covariates; sequential optimization of black-box functions; and a new Monte Carlo method...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2007