“Generally optimization includes finding “best available” values of some objective function given a defined domain (or input), including a variety of different types of objective functions and different types of domains.
It means find the best solution with the minimum effort.”
– Optimization, Wikipedia
Engineers are everyday surrounded by problems, that we can call “optimization problems”, whose nature is inherently complex:
the elements composing the problem have very strict and dependent relationship, and a slight change of a single element can rapidly affect the state of the others, often in a non-proportional way.
With modern times, also the number of elements composing the problem is growing significantly, and researchers needs to deal with hundreds of variables simultaneously.
So for people is extremely hard, if not impossible, to manage this complexity, controlling and directing the result where they need to go.
Optimization and regression analysis come to help: their sophisticated algorithms are able to identify the relationship and unkown functions behind a given problem and, once this is done, to direct the solution toward the goal (the best solution) maximizing the performance of the system.
A wide choiche of algorithms
The way to identify the optimal solution is a very complex science.
Over the years hundreds of algorithms have been developed like: radial basis functions, krigging, gradient methods, neural networks, genetic algorithms, evolutionary algorithms, stochastics, and any hybrid form.
Each of them is used for particular kind of problems, that are often classified from their mathematical point of view.
Don’t worry: IMPROVEit makes the choice automatically!
Particularly interesting are the problems classified as: blackbox and costly.
Black-box and costly problems
A black-box problem is a problem in which the mathematical relationship between input data and results is unkown (like for medical database analysis) or known but for which the complexity of resolution is so high as to be considered as unknown (as for any engineering problem involving differential equations system).
In particular, in engineering problems, the time needed to obtain the solution is often very long (hours or days) as in the case of CFD or FEM problems. In these cases the problem is called “costly”, because getting the solution costs a large time.
With costly functions is not possible to take advantage on a large number of samples to discover the underlying relationship, and algorithms needs to be particularly smart to find the optimal solution within a very few trials.
Our optimization algorithm is particularly optimized for black-box and costly functions and offers the most modern solution for engineers and scientists.
Thanks to IMPROVEit you can forget waiting days, optimization comes quickly!