problem.getPoolSlacks
slacks = problem.getPoolSlacks(num, *constraints)
|
num
|
The index of the solution in the pool, from
0 to
problem.attributes.poolsize
-1. Solutions are ordered from best to worst objective value, so index
0 is the solution with the best objective value found. May be passed positionally or as the keyword
num; when passed as a keyword, every positional argument selects a value.
|
|
constraints
|
(optional) constraint objects whose slacks will be returned. If none is provided, a list of slacks for all constraints in the problem will be returned.
|
|
slacks
|
A list of slack values if
*constraints contains more than one constraint object or is not provided, a single slack value otherwise.
|
import xpress as xp
p = xp.problem()
x = p.addVariables(5, vartype=xp.binary)
knapsack = xp.Sum(x) <= 2
p.addConstraint(knapsack)
p.setObjective(xp.Sum((5 - i) * x[i] for i in range(5)), sense=xp.ObjSense.MAXIMIZE)
p.controls.poolenumstrategy = xp.PoolEnumStrategy.FULL # enumerate beyond the optimum
p.optimize()
for i in range(p.attributes.poolsize):
print(i, p.getPoolSolObjVal(i), p.getPoolSlacks(i, knapsack))
The slacks are always returned in the input space, even if the problem is currently presolved.
The solution pool cannot be accessed from within a callback.
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