#12091: bug in add_constraint to MixedIntegerLinearProgram
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   Reporter:  dimpase             |          Owner:  ncohen  
       Type:  defect              |         Status:  new     
   Priority:  critical            |      Milestone:  sage-5.0
  Component:  linear programming  |       Keywords:          
Work_issues:                      |       Upstream:  N/A     
   Reviewer:                      |         Author:          
     Merged:                      |   Dependencies:          
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Description changed by ppurka:

Old description:

> constraints with 0 on one size of an inequality get lost, somehow:
> {{{
> sage: p = MixedIntegerLinearProgram(maximization=True)
> sage: A = p.new_variable()
> sage: p.add_constraint(A[0]==1)
> sage: p.add_constraint(0<= A[1]-A[0])
> sage: p.show()
> Maximization:
>
> Constraints:
>   1.0 <= x_0 <= 1.0
> Variables:
>   x_0 is a continuous variable (min=0.0, max=+oo)
>   x_1 is a continuous variable (min=0.0, max=+oo)
> }}}
>
> homogenizing the constraint fixes this problem:
> {{{
> sage: p.add_constraint(0*A[0]<= A[1]-A[0])
> sage: p.show()
> Maximization:
>
> Constraints:
>   1.0 <= x_0 <= 1.0
>   x_0 -x_1 <= 0.0
> Variables:
>   x_0 is a continuous variable (min=0.0, max=+oo)
>   x_1 is a continuous variable (min=0.0, max=+oo)
> }}}

New description:

 constraints with 0 on one size of an inequality get lost, somehow:
 {{{
 sage: p = MixedIntegerLinearProgram(maximization=True)
 sage: A = p.new_variable()
 sage: p.add_constraint(A[0]==1)
 sage: p.add_constraint(0<= A[1]-A[0])
 sage: p.show()
 Maximization:

 Constraints:
   1.0 <= x_0 <= 1.0
 Variables:
   x_0 is a continuous variable (min=0.0, max=+oo)
   x_1 is a continuous variable (min=0.0, max=+oo)
 }}}

 homogenizing the constraint fixes this problem:
 {{{
 sage: p.add_constraint(0*A[0]<= A[1]-A[0])
 sage: p.show()
 Maximization:

 Constraints:
   1.0 <= x_0 <= 1.0
   x_0 -x_1 <= 0.0
 Variables:
   x_0 is a continuous variable (min=0.0, max=+oo)
   x_1 is a continuous variable (min=0.0, max=+oo)
 }}}

 The bug is in `sage.numerical.mip.LinearConstraint` and
 `sage.numerical.mip.LinearFunction`. More examples:
 {{{
 sage: p = MixedIntegerLinearProgram()
 sage: b = p.new_variable()
 sage: b[0] <= b[1] <= 2  # This is not ok
 x_1 <= 2
 sage: (b[0] <= b[1] <= 2).constraints # Not ok
 [x_1, 2]
 sage: b[0] >= b[1] # This is ok
 x_1 <= x_0
 sage: 1 >= b[1]    # This is not since it starts with a constant
 False
 sage: 1 >= b[1] >= 2*b[0] # Not ok
 False
 sage: b[2] >= b[1] >= 2*b[0]  # Not ok
 2 x_0 <= x_1
 }}}

--

-- 
Ticket URL: <http://trac.sagemath.org/sage_trac/ticket/12091#comment:3>
Sage <http://www.sagemath.org>
Sage: Creating a Viable Open Source Alternative to Magma, Maple, Mathematica, 
and MATLAB

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