I have a table with features = {A,B}. B is a column of integers. Scanning the table, when I have a value change in B column, I increment a variable "changes" of 1:
if data[i,B]!=data[i-1,B]
then changes=changes+1
I want to find an order that minimizes changes and at the same time keep the repetition of a value in B in [0,upper_bound]. I'm thinking to use an array as a decision variable where save the position j for the element i:
order[i]=j means i element in data is the j-th element in ordering.
How can I model with constraint? This is what I do until now:
array[1..n, Features] of int: data;
int: changes=0;
constraint
forall(i in 1..n) (
if data[i,B] != data[i-1,B] then
changes=changes+1
endif
)
;
minimize changes;
I think I'm wrong using changes as a constant variable, right? Thank you in advance.
In MiniZinc (and in constraint programming in general) you cannot increment a variable as changes=changes+1).
If changes is a variable used only for the total count of changes you can use sum instead, something like:
% ...
var 0..n: num_changes;
constraint
changes = sum([data[i,B] != data[i-1,B] | i in 2..n])
;
% ...
However, if you want to use the number of accumulated changes for each i then you have to create a changes array to collect the values for each step, e.g.
var[1..n-1] of var 0..n: changes;
% the total number of changes (to minimize)
var 0..n-1: total_changes = changes[n-1];
constraint
forall(i in 1..n-1) (
if data[i,B] != data[i-1,B] then
changes[i] = changes[i-1]+1
else
changes[i] = changes[i-1]
endif
)
;