Preliminary Exploration Methods: The explorative phase is important in order to determine the behaviour and the main characteristics of the problem that we are examining. The principal aim is to get the most relevant qualitative information from a database of experiments making the smallest possible number of evaluations. More...

Schedulers: Instead of using a legion of public-domain algorithms, modeFRONTIER does optimization by using a selected number of highly efficient and proprietary algorithms. Most of the optimization techniques are covered: gradient based, genetic algorithms, evolution strategy algorithms, simulated annealing, RSM based optimizers. More...

Metamodeling: In those cases where the simulation run takes hours or days, using modeFRONTIER you can take advantage by replacing your real solver with a virtual model obtained by training the so-called response surfaces. This will allow you the run of a direct optimization otherwise impossible. More...

Single and Multiobjective Optimization: modeFRONTIER is the only commercial product on the market that has been built from the ground up to solve multiobjective optimization and multiobjective robust design optimization problems. Accordingly, modeFRONTIER can handle very efficiently several goals and constraints at the same time, allowing you to pick the best design from a family of designs that represent the best designs for various trade-offs. More...

Decision Support Tool: After having found some solutions of the multiobjective optimization problem, you come up against some difficulties: even though many efficient solutions exists only one or a reduced number of final solutions must be selected. Ranking between alternatives is a common and difficult task especially when several solutions are available or when many objectives or decision makers (DMs) are involved. This tool assists DMs for making coherent choices among reasonable alternatives. More...

Robust Design Optimization: Traditional optimization techniques tend to "over-optimize", producing solutions that perform well at the design point but have poor off-design characteristics. With robust design optimization it is possible to achieve the best stable solution. More...