Please help, how I can solve it?

回答済み

Konstantin Okunev

2021年01月14日 11:54 編集済み

• 
• 

Hi, all.

I have expression

exp = c_2.T@y - (b - A@u).T@lmbd

where 

b = np.array([50,40,30 + l,d_lim]).reshape((4,))

A = np.array([
[1.1,1.5,0.8],
[3,2.5,0.7],
[2,1,1.3],
[0,0,0]
])

u = m.addMVar(3,name='leader_strat')

lmbd = m.addMVar(4,name='lambda')

I want use m.setObjective( exp ) but I have error for transpose.

 

1

• 正式なコメント

  

  Simranjit Kaur

  • Gurobi Staff

  2024年12月06日 00:37

  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 why not try our AI Gurobot?.
• 

  Jaromił Najman

  • Gurobi Staff

  2021年01月14日 15:45

  Hi Konstantin,

  In the following, I omit \(c_2\) and \(y\), because both variables are not defined in your code snippet.

  The expression you try to construct is

  \[(b-A \cdot u)^T \cdot \lambda = \sum_{i=1}^4 \left( \lambda_i \cdot \left(b_i - \sum_{j=1}^3 ( A_{i,j}\cdot u_j ) \right) \right) \]

  which not a matrix object. The Python Matrix API is not meant to perform matrix operations but to construct matrix expression. For more information, see Gurobi Python Interface and Python Matrix Example.

  Note that the above expression is a quadratic one, so it might be advantageous to split it into a linear and a quadratic part

  import gurobipy as gp
  from gurobipy import GRB
  import numpy as np
  
  b = np.array([50,40,33,44]).reshape((4,))
  A = np.array([
  [1.1,1.5,0.8],
  [3,2.5,0.7],
  [2,1,1.3],
  [0,0,0]])
  
  u = m.addVars(3,name='leader_strat')
  lmbd = m.addVars(4,name='lambda')
  
  lExpr = gp.LinExpr(0)
  qExpr = gp.QuadExpr(0)
  for i in range(4):
    lExpr.add(lmbd[i],b[i])
    for j in range(3):
      qExpr.add(lmbd[i] * u[j], A[i][j])
  
  finalExpr = lExpr - qExpr
  
  # Set objective
  m.setObjective(finalExpr, GRB.MINIMIZE)

  Note that your model is a non-convex quadratic one, so you have to set the NonConvex parameter to 2.

  m.setParam("NonConvex",2)

  Best regards,
  Jaromił

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