Dear All,
I am trying to create a scheduling for semiconductor cluster tool by using CPLEX library (python).
However I encountered error for the constraint.

Here is the code:



------------------------------
Nicholas Nicholas
------------------------------

#DecisionOptimization

Hi,

from docplex.mp.model import Model
import math

m = Model(name='Scheduling')

K = [number for number in range(1, math.factorial(6)+1)] #720
totalK = len(K)

xi = m.continuous_var_list(totalK+1,name = 'xi', lb = 0)
xj = m.continuous_var_list(totalK+1,name = 'xj', lb = 0)

 

P = 8 
T = 6 
r1 = 100 
r2 = 200 
v = 1 
w = 1 

PLACES = ([("p1", v+w,0, None),
           ("p2", w+r1,0, None),
           ("p3", 0,1, None),
           ("p4", v+w,0, None),
           ("p5", w+r2,0, None),
           ("p6", 0,1, None),
           ("p7", w+v,0, None),
           ("p8", 0, 1, None)])

for k in K:
  for p in PLACES:
    m.add_constraint(xj[k] - xi[k] >= p[1] - p[2]) ​

works fine

continuous_var is a scalar variable but you seem to need an array instead

------------------------------
[Alex] [Fleischer]
[Data and AI Technical Sales]
[IBM]
------------------------------

Original Message:
Sent: Sat July 02, 2022 02:33 AM
From: Nicholas Nicholas
Subject: CPLEX grammar for scheduling case

Dear All,
I am trying to create a scheduling for semiconductor cluster tool by using CPLEX library (python).
However I encountered error for the constraint.

Here is the code:

m = Model(name='Scheduling')

inf = docplex.cp.expression.INFINITY

bigM= 1000000

url = None

key = None

numbers = range(1, math.factorial(6))

K = [number for number in range(1, math.factorial(6)+1)] #720

totalK = len(K)

xi = m.continuous_var(name = 'xi', lb = 0)

xj = m.continuous_var(name = 'xj', lb = 0)

obj_lambda = m.continuous_var(name = 'lambd', lb = 0)

P = 8 

T = 6 

r1 = 100 

r2 = 200 

v = 1 

w = 1 

PLACES = ([("p1", v+w,0, None),

           ("p2", w+r1,0, None),

           ("p3", 0,1, None),

           ("p4", v+w,0, None),

           ("p5", w+r2,0, None),

           ("p6", 0,1, None),

           ("p7", w+v,0, None),

           ("p8", 0, 1, None)])

for k in K:

  for p in PLACES:

    m.add_constraint(xj[k] - xi[k] >= p(1) - p(2)*obj_lambda) 
TypeError: 'Var' object is not subscriptable

Can anyone help me, please? Thank you in advance.

------------------------------
Nicholas Nicholas
------------------------------

#DecisionOptimization