ModeFrontier

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modeFRONTIER is a multidisciplinary design optimization and multi-objective optimization and design environment, written to allow easy coupling to almost any computer aided engineering (CAE) tool whether commercial or in-house. Created by Esteco, modeFRONTIER provides an environment which allows product engineers and designers to integrate their various CAE tools, such as CAD, Finite Element Structural Analysis and Computational Fluid Dynamics (CFD) software. modeFRONTIER is a GUI driven wrapper around the CAE tool, performing the optimization by modifying the value assigned to the input variables, and analyzing the outputs as they can be defined as objectives and/or constraints of the design problem.

1 History
2 Process integration
3 Design optimization
4 Robust design optimization
5 Just for fun
6 External links

[edit] History

Esteco was created in 1999 to transfer the knowledge acquired by its founders while working on a European Union sponsored project on Design Optimization (FRONTIER, started in 1996) into a commercial product, called modeFRONTIER. In 2001, modeFRONTIER version 2.4 become a global player among the MDO/PIDO tools, being one of the first to enable true multi-objective optimization through Pareto dominance criteria. The latest release is version 4.0 (February 2008).

[edit] Process integration

The logic of the optimization loop can be set up in a clear graphical way, building up a "workflow" structure by means of interconnected nodes. Serial and parallel connections and conditional switches are available. modeFRONTIER builds automatic chains and steers many different external application programs using scripting (DOS script, UNIX shell, Python programming language, Visual Basic, JavaScript,etc...) and direct integrations nodes (with many CAE/CAD and other application programs).

[edit] Design optimization

modeFRONTIER includes design of experiments (DOE), optimization algorithms and robust design tools, that can be combined and blended to build up the most efficient strategy to solve also complex multi-disciplinary problems. Together with the ease-of-use of the program, this is the strong point of the software.

[edit] Design of experiments

Different strategies are available, spanning from random generator sequences to Factorial DOEs, including Orthogonal and Iterative Techniques, as like as D-Optimal or Cross Validation. Monte Carlo is available for robustness analysis.

[edit] Multi objective algorithms

Among the others, different implementations of genetic algorithm, game theory, simulated annealing, evolution strategies are able to manage continuous, discrete and mixed variable problems. More classical mono-objective algorithms are as well available, as like as gradient-based methods or simplex algorithm.

[edit] Response surfaces

Different response surface methodology techniques are available to interpolate data and perform so called "virtual optimizations", particularly useful when the optimization applies to problems where every fitness function evaluation is time-expensive. Singular value decomposition and Polynomial Responses are implemented, as well as the more sophisticated kriging, neural network and Gaussian process ones.

[edit] Data processing and multiple criteria decision making (MCDM)

This set of tools enables the user to explore, filter and rank the set of optimal solutions of a multi-objective problem (the so-called Pareto frontier), to perform sensitivity analyses, robustness verifications and also to produce standard and customizable reports of the optimization project (RTF,PDF,HTML formats).

[edit] Robust design optimization

This is the latest step of MDO towards 6 Sigma: optimizing a design taking into account uncertainties and tolerances. RSM techniques can be used to overcome the increase in time-expense due to this extensive statistic approach.