Solution of optimization saved as array.

回答済み

Fatima Ezzahra El habibi

2022年05月16日 08:02 編集済み

• 
• 
• 

Hello everyone. I am new at programming and I've been struggling with this piece of code. I am working with a modified version of the Knapsack Problem.

 

• #Data

n = n. of items

weights =[...]
v = [...] 

sigma =[...]




knapsack_model = Model('knapsack')
x = knapsack_model.addVars(n, vtype = GRB.BINARY, name="x")

# constraint on capacity
knapsack_model.addConstr(sum(weights[i]*x[i] for i in range(n)) <= C)

estimation = [ ]

for i in range(n):
    values = np.random.normal(v[i], sigma[i])
    estimation.append(values)

# Objective function
obj_fn = sum((estimation[i]*x[i]) for i in range(n))
knapsack_model.setObjective(obj_fn, GRB.MAXIMIZE)

knapsack_model.optimize()
print('Optimization is done. Objective Function Value: %.2f' % knapsack_model.objVal)

 

#Piece of code that gives me an error
total = [ ]
for v in knapsack_model.getVars():
    total.append(v.x)

final_objective = sum((total[ i ]*v[ i ]) for i in range(n))

Here I get an error saying: 'Var' object is not subscriptable

I need to use the x that gurobi produced and multiply it with v[i], but I am having a hard time putting the x in an array that i can use.

 

If anyone could help me I would really appreciate it.

Thank you in advance!

0

• 正式なコメント

  

  Simranjit Kaur

  • Gurobi Staff

  2025年11月16日 23:44

  This post is more than three years old. Some information may not be up to date. For current information, please check the Gurobi Documentation or Knowledge Base. If you need more help, please create a new post in the community forum, or try Gurobot, our chatbot interface offering instant, expert-level support.
• 

  Jaromił Najman

  • Gurobi Staff

  2022年02月01日 17:09

  You are using the variable \(\texttt{v}\) in the \(\texttt{for}\)-loop

  for v in knapsack_model.getVars():
      total.append(v.x)

  but you have already defined and used \(\texttt{v}\) before. Using a different iterator in the above \(\texttt{for}\)-loop should solve the issue.

  for var in knapsack_model.getVars():
      total.append(var.x)

  Best regards, 
  Jaromił

  1

投稿コメントは受け付けていません。