A modular system of algorithms for unconstrained minimization
ACM Transactions on Mathematical Software (TOMS)
Algorithm 755: ADOL-C: a package for the automatic differentiation of algorithms written in C/C++
ACM Transactions on Mathematical Software (TOMS)
ADIC: an extensible automatic differentiation tool for ANSI-C
Software—Practice & Experience
Algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound-constrained optimization
ACM Transactions on Mathematical Software (TOMS)
Recipes for adjoint code construction
ACM Transactions on Mathematical Software (TOMS)
IMPACT of Computing in Science and Engineering
Evaluating derivatives: principles and techniques of algorithmic differentiation
Evaluating derivatives: principles and techniques of algorithmic differentiation
NEOS and Condor: solving optimization problems over the Internet
ACM Transactions on Mathematical Software (TOMS)
A case study in the performance and scalability of optimization algorithms
ACM Transactions on Mathematical Software (TOMS)
Automatic differentiation of algorithms: from simulation to optimization
Automatic differentiation of algorithms: from simulation to optimization
iNEOS: an interactive environment for nonlinear optimization
Applied Numerical Mathematics - Applied and computational mathematics: Selected papers of the third panamerican workshop Trujillo, Peru, 24-28 April 2000
Adifor 2.0: Automatic Differentiation of Fortran 77 Programs
IEEE Computational Science & Engineering
IEEE Computational Science & Engineering
Overture: An Object-Oriented Framework for Solving Partial Differential Equations
ISCOPE '97 Proceedings of the Scientific Computing in Object-Oriented Parallel Environments
Solving large-scale optimization problems with EFCOSS
Advances in Engineering Software
EFCOSS: An interactive environment facilitating optimal experimental design
ACM Transactions on Mathematical Software (TOMS)
Evaluation of a computer model for wavy falling films using EFCOSS
ICCSA'03 Proceedings of the 2003 international conference on Computational science and its applications: PartII
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Numerical simulation is a powerful tool in science and engineering, and it is also used for optimizing the design of products and experiments rather than only for reproducing the behavior of scientific and engineering systems. In order to reduce the number of simulation runs, the traditional "trial and error" approach for finding near-to-optimum design parameters is more and more replaced with efficient numerical optimization algorithms. Done by hand, the coupling of simulation and optimization software is tedious and error-prone. In this note we introduce a software environment called EFCOSS (Environment For Combining Optimization and Simulation Software) that facilitates and speeds up this task by doing much of the required work automatically. Our framework includes support for automatic differentiation providing the derivatives required by many optimization algorithms. We describe the process of integrating the widely used computational fluid dynamics package FLUENT and a MINPACK-1 least squares optimizer into EFCOSS and follow a sample session solving a data assimilation problem.