# Number of objectives

The number of objectives to be minimised plays a crucial part in the technique to be used, along with 
the time needed for a given code to converge and provide results. The main idea behind this small 
discussion is to identify the needs when starting an analysis.

- One objective or more than one but they are not antagonistic: a single objective optimisation can 
be done. When dealing with several criteria the idea is then to combine them into an homemade criteria, 
based on whatever recipe one wants to apply (weighted/unweighted criteria, L1 or L2 sum, ...). From 
there, the use of `TNlopt` algorithm is recommended.

- More than one objective that cannot be combined. In this case, the approach recommended would be to 
use Vizir which contains multi and many objectives algorithms. The difference between multi and many 
is tidious and is oftenly set between 3 and 4. A discussion between these algorithm is provided in 
{{metho}}.