[英]how to write a conditional constraint in CPLEX python?
我有一個 model,它有一個二進制變量 x [i] [j] [k]。 我需要添加一個滿足這個條件的約束:
if x[i][j][k1]==1 and x[j][i][k2]==1
Then:
k2-k1>8
我有這段代碼,但我認為它不正確:
mdl.add((y[(i,j,k)]+y[(j,i,k1)]==2),(k1-k>8) )
我也,把這個:
mdl.add(mdl.if_then(y[(i,j,k1)]+y[(j,i,k2)]==2, k2-k1>8))
但我收到了這個錯誤:
raise DOcplexException(resolved_message)
DOcplexException: Expecting linear constraint, got: False
我怎么能用 cplex python API model 這個?
讓我分享一下 if then 的例子
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)
如果你想看到並且在 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)
你也可以重寫
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)
Model.if_then
鏈接兩個線性約束。 如果第一個滿意,第二個也會滿意。
就您而言,我了解在k2-k1>8
中不涉及決策變量。 所以這完全取決於數據,在 model 構建時已知。
在這種情況下,因果關系反過來:如果 k2-k1>8,則 x[i,j,k1] 和 x[i,j,k2] 都必須等於 1。
那么最簡單的代碼是:
if k2-k1>8:
m.add(x[i,j,k1] == 1)
m.add(x[i,j,k2] == 1)
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