问题
I have a model that has one binary variable x [i] [j] [k]. I need to add a constraint that fullfils this condition:
if x[i][j][k1]==1 and x[j][i][k2]==1
Then:
k2-k1>8
I have this code but I assum it is not correct :
mdl.add((y[(i,j,k)]+y[(j,i,k1)]==2),(k1-k>8) )
I also, put this:
mdl.add(mdl.if_then(y[(i,j,k1)]+y[(j,i,k2)]==2, k2-k1>8))
but I got this error:
raise DOcplexException(resolved_message)
DOcplexException: Expecting linear constraint, got: False
How can I model this with cplex python API?
回答1:
let me share the if then example from
https://www.linkedin.com/pulse/making-optimization-simple-python-alex-fleischer/
from docplex.mp.model import Model
mdl = Model(name='buses')
nbbus40 = mdl.integer_var(name='nbBus40')
nbbus30 = mdl.integer_var(name='nbBus30')
mdl.add_constraint(nbbus40*40 + nbbus30*30 >= 300, 'kids')
mdl.minimize(nbbus40*500 + nbbus30*400)
mdl.solve()
for v in mdl.iter_integer_vars():
print(v," = ",v.solution_value)
print()
print("with if nb buses 40 more than 3 then nbBuses30 more than 7")
#if then constraint
mdl.add(mdl.if_then(nbbus40>=3,nbbus30>=7))
mdl.minimize(nbbus40*500 + nbbus30*400)
mdl.solve()
for v in mdl.iter_integer_vars():
print(v," = ",v.solution_value)
and if you want to see and in the if
from docplex.mp.model import Model
mdl = Model(name='buses')
nbbus40 = mdl.integer_var(name='nbBus40')
nbbus30 = mdl.integer_var(name='nbBus30')
mdl.add_constraint(nbbus40*40 + nbbus30*30 >= 300, 'kids')
mdl.minimize(nbbus40*500 + nbbus30*400)
mdl.solve()
for v in mdl.iter_integer_vars():
print(v," = ",v.solution_value)
print()
print("with if nb buses 40 more than 3 and less than 7 then nbBuses30 more than 7")
#if then constraint
mdl.add(mdl.if_then((nbbus40>=3) + (nbbus40<=7)>=2,nbbus30>=7))
mdl.minimize(nbbus40*500 + nbbus30*400)
mdl.solve()
for v in mdl.iter_integer_vars():
print(v," = ",v.solution_value)
which you can also rewrite
from docplex.mp.model import Model
mdl = Model(name='buses')
nbbus40 = mdl.integer_var(name='nbBus40')
nbbus30 = mdl.integer_var(name='nbBus30')
mdl.add_constraint(nbbus40*40 + nbbus30*30 >= 300, 'kids')
mdl.minimize(nbbus40*500 + nbbus30*400)
mdl.solve()
for v in mdl.iter_integer_vars():
print(v," = ",v.solution_value)
print()
print("with if nb buses 40 more than 3 and less than 7 then nbBuses30 more than 7")
#if then constraint
mdl.add((((nbbus40>=3) + (nbbus40<=7)>=2))<=(nbbus30>=7))
mdl.minimize(nbbus40*500 + nbbus30*400)
mdl.solve()
for v in mdl.iter_integer_vars():
print(v," = ",v.solution_value)
回答2:
Model.if_then
links two linear constraints left-to-right. If the first one becomes satisfied, the second will be satisfied too.
In your case , I understand that in k2-k1>8
there are no decision variables involved. SO this is purely data-dependent, known at model build time.
In that case, the causality works the other way round: if k2-k1>8 then both x[i,j,k1] and x[i,j,k2] must be equal to 1.
The simplest code is then:
if k2-k1>8:
m.add(x[i,j,k1] == 1)
m.add(x[i,j,k2] == 1)
来源:https://stackoverflow.com/questions/62388899/how-to-write-a-conditional-constraint-in-cplex-python