[Bonmin] boncouenne crash

[Francois Dionne]

Dear mailing list,

I just got an error message when I try to solve a nonconvex MINLP problem using boncouenne from within an AMPL script.

There are four files attached to this message:
mymodel.mod is the AMPL model,
tmp.dat is the data file,
myscript.txt is the AMPL script,
log.txt is the captured output of AMPL when it calls boncouenne .

The script is called with:
ampl myscript.txt
,which sets boncouenne as the solver, then the model and data files are loaded before solving.

I'm using boncouenne downloaded by SVN from trunk on 11 august 2008. My OS is Ubuntu Linux Hardy Heron.

Your advice will be appreciated.
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bonmin: 
ANALYSIS TEST: objectives:
min (-( +1*x_0))
constraints:
(y_2*((x_0*log((1+x_0)))-x_1)) = -0
((y_4*((x_0*log((1+x_0)))-x_1))+(y_3*((x_0-log((1+x_0)))+(-0.5*x_1)))) = -0
(y_3*((x_0*log((1+x_0)))-x_1)) = -0
((-((1+x_0)*(log((1+x_0))^2))) +1*x_1) <= -0
-0 <= ((-(log((1+x_0))^2)) +1*x_1)
variables:
x_0 [ 0.05 , 1 ]
x_1 [ -inf , inf ]
y_2 [ -3656 , -1 ] integer
y_3 [ -6 , 6 ] integer
y_4 [ -55 , 35 ] integer
end
Problem size before standarization: 5 variables (3 integer), 5 constraints.
Problem size after  standarization: 20 variables (3 integer), 5 constraints.

******************************************************************************
This program contains Ipopt, a library for large-scale nonlinear optimization.
 Ipopt is released as open source code under the Common Public License (CPL).
         For more information visit http://projects.coin-or.org/Ipopt
******************************************************************************

NLP0012I 
              Num      Status      Obj             It       time
NLP0013I     1        OPT         -1.000000007065575      33       0.028002
boncouenne: CbcModel.cpp:9880: double CbcModel::checkSolution(double, double*, int, double): Assertion `fabs(value-solution[iColumn]) <= integerTolerance' failed.
NLP0013I     2        OPT         -1.00000000837105       6        0.004001
error running boncouenne:
	termination code 6
<BREAK>
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option solver boncouenne;
model mymodel.mod;
data tmp.dat;
solve;
if match(solve_message,'Infeasible')>0 then {print 0 >output.txt;}
else if match(solve_message,'Optimal')>0 then {print 1 >output.txt;print {i in 1..4} x[i] >output.txt;}
else {print 3 >output_tmp.txt;print solve_message >output.txt;}
quit;

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