Writing belongs to constraint with gurobipy

Ongoing

Venkateswarlu Yampati

• November 07, 2022 20:06

I am trying to add this constraint to my model.

I have added all the constraints except the last one. How to write this constraint when a variable belongs to a set. Thanks

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  Jaromił Najman

  Gurobi Staff

  • November 08, 2022 09:09

  Could you post a minimal working example of what you are currently trying to implement?

  How to write this constraint when a variable belongs to a set.

  Depending on how you define your variable in your code, you can define a list of indices and loop over those, e.g.,

  import gurobipy as gp
  
  m=gp.Model()
  x = m.addVars(10)
  
  U = [0,1,2,3]
  m.addConstrs((x[u] <= 2) for u in U)

  constructs the constraints \( x_u \leq 2 \quad u \in U = \{0,1,2,3\}\).

  Best regards, 
  Jaromił

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  Venkateswarlu Yampati

  • November 11, 2022 18:36

  

  

  Hi Jaromil,

  Thanks for the reply. Here is the problem I am trying to solve:

  U_1 = {1,2,3,..L}

  U_2 = {1,2,3,..K}

  R=

  r^{u}_{t,f} is the cost function. I have to maximize the above objective function using constraints C1,C2, and C3 in the above problem I have posted before. Here is the code I wrote:

  T = (np.arange(1,21,1))
  #print(len(T))
  F = (np.arange(1,101,1))
  M = np.arange(1,11,1)
  E = (np.arange(1,6,1))
  U = (np.arange(1,6,1))

  
  assignment_model = grb.Model('Assignment')

     x =  assignment_model.addVars(M.shape[0], T.shape[0], F.shape[0], vtype = grb.GRB.CONTINUOUS, lb = 0, ub = 1,name = 'x')
      assignment_model.addConstrs((sum(x[u, t, f]  for u in range(E.shape[0]) for u in range(U.shape[0])) <= 1 for t in range(T.shape[0]) for f in range(F.shape[0])), name = 'one RB allocation')
      assignment_model.addConstrs((sum(x[u,t,f] for t in range(T.shape[0]) for f in range(F.shape[0])) >= 1 for u in range(U.shape[0]) ), name = 'latency requirement') 
      obj_fun = sum(se_e_power[p][u,t,f] * x[u,t,f] for u in range(E.shape[0]) for t in range(T.shape[0]) for f in range(F.shape[0])) + sum(se_u_power[p][u,t,f] * x[u,t,f] for u in range(U.shape[0]) for t in range(T.shape[0]) for f in range(F.shape[0]))
      assignment_model.setObjective(obj_fun, grb.GRB.MAXIMIZE)
      assignment_model.setParam('OutputFlag', False)
      assignment_model.optimize()
      #print('Optimization is done. Objective function value: %.2f' % assignment_model.objVal)
      value = assignment_model.objVal

  It looks like I wrote the third constraint as you suggested. But the output is not as expected. Please let me know if there is anything wrong with code.

  Thanks

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  Jaromił Najman

  Gurobi Staff

  • November 14, 2022 09:40

  Hi Venkateswarlu,

  The constraint

  assignment_model.addConstrs((sum(x[u,t,f] for t in range(T.shape[0]) for f in range(F.shape[0])) >= 1 for u in range(U.shape[0]) ), name = 'latency requirement')

  Looks OK. Did you write the model to an LP file and inspect it to see whether all constraints look as expected?

  assignment_model.write("myLP.lp")

  The write method will write a human-readable LP file which you can inspect.

  Best regards, 
  Jaromił

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  Venkateswarlu Yampati

  • November 14, 2022 16:22

  

  

  Hi Jaromil,

  I am using the write command, but I do not see any output. I updated the version to latests but I do not see any output.

  Any suggestions?

  Thanks,

  Venkat

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  Jaromił Najman

  Gurobi Staff

  • November 14, 2022 16:30

  Hi Venkat,

  The write method will generate a file in the folder from which you execute your script. It will not print anything to the console output or the log.

  Best regards, 
  Jaromił

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  Venkateswarlu Yampati

  • November 14, 2022 16:30

  

  

  I can see the output now

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  Venkateswarlu Yampati

  • November 24, 2022 15:23

  

  

  Hi,

  I guess I solved the issue after printing it. Thanks for the suggestions.

  One more question is what kind of algorthim the libraray is using. As my problem is convex optimization, I was looking into theorteical concept of solving the problem. It was explained there are many algorthims to solve it. What exactly the algorthim it uses when I write grb. Maximize(like sub-gradient or Newtons or lagrangian). Is there any documentation which explains the algaorthim the library is using?

  Thanks,

  Venkat

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  Jaromił Najman

  Gurobi Staff

  • November 25, 2022 08:29

  Hi Venkat,

  You can find some basics on convex continuous programming at Linear Programming (LP) - A Primer on the Basics. There at the bottom, you will find the literature for the algorithms you seek.

  Best regards, 
  Jaromił

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  Venkateswarlu Yampati

  • November 29, 2022 13:58

  

  

  Hi Jaromil,

  Thanks for the information.

  I have a quick one. I am trying to write the following constraint but I am getting an error. Could you suggest me how to write the following expression? t,f are for all. R_min is a constant. 

  

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