[Ipopt] [SCIP] SCIP and Ipopt

[Vincent Mirian]

Hi all.

Thanks for the reply Benny.

I created the following input file to the framework.
STATISTICS
  Problem name     : test.cip
  Variables        : 5 (0 binary, 5 integer, 0 implicit integer, 0
continuous)
  Constraints      : 0 initial, 5 maximal
OBJECTIVE
  Sense            : minimize
VARIABLES
  [integer] <c#0b#0>: obj=0, original bounds=[0,1]
  [integer] <c#1b#0>: obj=0, original bounds=[0,1]
  [integer] <c#0b#1>: obj=0, original bounds=[0,1]
  [integer] <c#1b#1>: obj=0, original bounds=[0,1]
  [integer] <y#0>: obj=0, global bounds=[0,4], local bounds=[0,4]
CONSTRAINTS
  [linear] <pack_1>: <c#0b#0>[I] +<c#0b#1>[I] == 1;
  [linear] <pack_2>: <c#1b#0>[I] +<c#1b#1>[I] == 1;
  [linear] <cap_0>: <c#0b#0>[I] +<c#1b#0>[I] <= 1;
  [linear] <cap_1>: <c#0b#1>[I] +<c#1b#1>[I] <= 1;
  [linear] <obj_0>: -<c#0b#1>[I]*<c#1b#1>[I]*1 -<c#0b#0>[I]*<c#1b#0>[I]*1
+4 -<y#0> == 0;
END

The results should assign y#0 to 4. However, I get the following output
(snippet of output to reduce length):

presolving (1 rounds: 1 fast, 1 medium, 1 exhaustive):
 5 deleted vars, 5 deleted constraints, 0 added constraints, 1 tightened
bounds, 0 added holes, 0 changed sides, 0 changed coefficients
 0 implications, 0 cliques
presolved problem has 0 variables (0 bin, 0 int, 0 impl, 0 cont) and 0
constraints
transformed objective value is always integral (scale: 1)
Presolving Time: 0.00

objective value:                                    0
c#0b#0                                              1 (obj:0)
c#1b#1                                              1 (obj:0)

The assignment of c#0b#0 and c#1b#1 are valid solutions. I am confused on
the reason that the objective value is 0. I am assume that the objective
value is y#0, since it is the only variable not stated. The value of y#0
should be 4.

Some guidance would be appreciated. Note that I searched the SCIP mailing
list archive but I did not find any references for the input format and
description of the output.

Any help would be appreciated. Thank you.



On Tue, Feb 13, 2018 at 11:38 PM, Benjamin Müller <benjamin.mueller at zib.de>
wrote:

> Hi Vincent,
>
> I would recommend using JSCIPOpt, which is our SCIP-Java interface that
> can be found here:
>
>     https://github.com/SCIP-Interfaces/JSCIPOpt
>
> All relevant steps for building the interface are listed in the
> INSTALL.md, but basically, you will need to download the latest SCIP
> Optimization Suite and compile it with Ipopt. You might want to have a look
> at the JSCIPOpt/examples/Quadratic, which shows how to model a problem with
> simple quadratic constraints.
>
> Please note that SCIP can't handle a nonlinear objective function. For
> this reason, you need to add an auxiliary variable z and then model your
> problem as
>
>     min z
>     z >= sum_{ij} X_{ij} Y_{ij}
>     ...
>
> Best,
> Benny
>
> On 02/13/2018 07:05 PM, Vincent Mirian wrote:
>
>> HI all.
>>
>> I am new to the SCIP community.
>>
>> I am looking for a non-linear solver to solve:
>> - an objective function similar to 0 <= sum over i and j of X_ij * Y_ij *
>> Constant < max
>> - with constraints similar tosum(X_ij) = 1 and sum(Y_ij) = 1 (forcing the
>> values of X_ij and Y_ij to zero or one). A solution would be sufficient (it
>> can be local or global optimal).
>>
>> I would need to interface the solver with Java. I found Google
>> Optimization Tools (OR-Tools) to interface SCIP with java. Note that this
>> work is for academic research.
>>
>> - Would SCIP or Ipopt be suitable for my task? Would anyone have
>> experience integrating SCIP or Ipopt into Java?
>> - I'm using a machine with ubuntu 64-bit. Are there any issues with
>> installing these tools in this machine environment?
>> - What is the manner to describe the constraints and objective function
>> using these tools?
>>
>> Thank you.
>> --
>> Vincent Mirian
>>
>>
>> _______________________________________________
>> Scip mailing list
>> Scip at zib.de
>> https://listserv.zib.de/mailman/listinfo/scip
>>
>>
> --
> ______________________________
> Benjamin Müller
> Zuse Institute Berlin
> Takustr. 7, 14195 Berlin
> benjamin.mueller at zib.de
> +49 30 841 85-195
>



-- 
Vincent Mirian
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