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Active, inactive and violated constraints, feasible set, and some other terms used in the optimization process are defined.
Since only concerned points of active and violated constraints are calculated accurately, the computational cost associated with non-probabilistic constraint is decreased significantly.
Moreover, the constraints are easily treated afterwards since the points with violated constraints can be recognized and classified (according to weak or hard constraints).
This excludes non-idempotent operators such as + which define problems which are very important in practical applications such as Max-CSP, where the aim is to minimise the number of violated constraints.
Hence, one way to find a constrained local minimum is to increase gradually the penalties of those violated constraints and to look for a local minimum of the penalty function using any existing algorithm until a solution to the constrained model is found.
Recall is a similar metric and shows the number of correctly predicted satisfied or violated constraints as a percentage of all satisfied or violated constraints.
Similar(12)
There is no satisfied constraint, nor violated constraint at the first example, state 001.
Note that for each violated constraint, there is an associated penalty to the fitness function.
In original version of algorithm the first most violated constraint is taken into consideration.
For each violated constraint, there is an associated penalty to the fitness function.
Regarding the violated constraint, three states shown in Table 1 are explained.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com