maximum_minimum
maximum_minimum |
Purpose
The maximum (resp) minimum constraint states that a variable z is the maximum (resp) minimum of a list of variables vars
Synopsis
minimum(vars) = z or maximum(vars) = z
z = minimum(vars) or z = maximum(vars)
Arguments
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vars
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list of decision variables: {set of cpvar | array(range) of cpvar | cpvarlist}
|
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z
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decision variable for the maximum/minimum: cpvar
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Return value
A maximum/minimum constraint over z and vars
Example
The following example shows how to use the maximum/minimum constraints:
model "Min and Max"
uses "kalis"
declarations
R = 1..5
x: array(R) of cpvar
v, w, y: cpvar
L: cpvarlist
MaxCtr: cpctr
end-declarations
setname(v,"v")
setname(w,"w")
setname(y,"y")
forall(i in R) do
setname(x(i),"x"+i+"")
setdomain(x(i), 0, 2*i + round(5*random + 0.5))
end-do
writeln("Initial domains:\n ", x, " ", v)
! Minimum constraint with automated posting
v = minimum(x)
writeln("With minimum constraint:\n ", x, " ", v)
x(1) = 2
writeln("Fixing x(1) to 2: ", v)
! Maximum constraint with explicit posting
MaxCtr:= w = maximum({x(2), x(3), x(5)})
if cp_post(MaxCtr) then
writeln("With maximum constraint:\n ", x, " ", w)
else exit(1)
end-if
w <= 7
writeln("Bounding w by 7:\n ", x, " ", w)
! Maximum constraint on list of variables
L += x(2); L += x(3); L += x(4)
y = maximum(L)
writeln("With 2nd maximum constraint:\n ", x, " ", y)
if (cp_find_next_sol) then
writeln("A solution:\n ", x, " ", v, " ", w, " ", y)
end-if
end-model