Specifications

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We shall return to the capabilities of the AnyChart in more detail in the next lesson
, which deals with the
definition of optimization studies.
Optimization studies
The parameter study introduced in the preceding lesson provides a complete overview of the design space,
but the study is only feasible when the problem has few independent parameters, preferably one or two. In
the previous lesson we considered a problem with two parameters and 5 steps in each direction of the
design space leading to 5^2 = 5 x 5 = 25 analyses. If the problem had 10 parameters we would be facing
5^10 = 9.7 million analyses, which is an entirely different matter in terms of computation times. The truth
is that such so-called full factorial parameter studies are computationally infeasible when the problem has
more than very few independent parameters. So what to do?
The solution is to use a method that picks the combinations to compute carefully and only has to evaluate a
few of them. One class of such methods is optimization. An optimization algorithm systematically searches
through the design space for the combination of parameters that minimizes the value of a function of the
parameters, the so-called objective function. Some algorithms also allow the definition of constraint
functions, which are dependent parameters that must be maintained below a certain upper limit.
The AnyBody Modeling System provides a study to handle optimization problems. The mathematical
definition of the problem it solves is as follows: