The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. DAKOTA contains algorithms for optimization with gradient and nongradientbased methods; uncertainty quantification with sampling, reliability, and stochastic finite element methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a reference manual for the commands specification for the DAKOTA software, providing input overviews, option descriptions, and example specifications.
@techreport{SAND2006-4055,
author = {Michael S. Eldred and Anthony A. Giunta and Shannon L. Brown and Brian M. Adams and Daniel M. Dunlavy and John P. Eddy and David M. Gay and Josh D. Griffin and William E. Hart and Patty D. Hough and Tammy G. Kolda and Monica L. Martinez-Canales and Laura P. Swiler and Jean-Paul Watson and Pamela J. Williams},
title = {{DAKOTA}, a Multilevel Parallel Object-oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 4.0 Reference Manual},
number = {SAND2006-4055},
institution = {Sandia National Laboratories},
month = {October},
year = {2006},
doi = {10.2172/895073},
url = {http://www.osti.gov/scitech/biblio/895073},
urldate = {2014-04-17},
}