Originally posted by: Zak86
Hi Cplex users,
Anyone may help me in this problem please ?
I have to minimize sum( x[i] ) where i in [1 .. N ] and x[ ] a binary array variable ( the output solution variable ) .
The, binary LP, original problem (x[] binary) gives me a logic solution with an optimal status and value = to 7 .
However, when relaxing the problem ( just to put x[ ] continuous in [0 1] using, in JAVA, IloConversion conversion1 = cplex.conversion(x, IloNumVarType.Float); cplex.add(conversion1); and without any other modification on constraints ) ,it gives me also optimal solution status, however with a value = to zero .
This latter "Relaxed" Solution value ( zero ) is really absurd ! First, because i have a very clear constraint in which we must have at least one x[i] <> 0 . Second, (even without considering this constraint) , if the Zero solution is the optimal one, the original binary problem must give this solution.
Note that when i read the output message, Cplex uses, automatically, the branch and bound/cuts method for the binary LP and uses the dual SIMPLEX for the relaxed LP.
These are the ends of the output log of the 1) ORIGINAL LP and 2) RELAXED LP .
1) OUTPUT log for the original LP ( x binary in { 0 , 1 } ):
Elapsed time = 12.76 sec. (5572.86 ticks, tree = 1.23 MB, solutions = 3)
2313 355 cutoff 7.0000 5.8042 144000 17.08%
Cover cuts applied: 56
Implied bound cuts applied: 62
Flow cuts applied: 4
Mixed integer rounding cuts applied: 18
Zero-half cuts applied: 11
Root node processing (before b&c):
Real time = 5.24 sec. (2120.75 ticks)
Parallel b&c, 4 threads:
Real time = 10.76 sec. (4851.85 ticks)
Sync time (average) = 0.00 sec.
Wait time (average) = 0.00 sec.
------------
Total (root+branch&cut) = 16.00 sec. (6972.60 ticks)
Solution pool: 3 solutions saved.
MIP - Integer optimal solution: Objective = 7.0000000000e+00
Solution time = 16.03 sec. Iterations = 154949 Nodes = 2749
Deterministic time = 6972.60 ticks (434.96 ticks/sec)
2) OUTPUT log for the RELAXED LP ( x continous in [ 0 , 1 ] ):
Reinitializing dual norms . . .
Markowitz threshold set to 0.1
Iteration log . . .
Iteration: 1 Dual objective = 0.000000
Markowitz threshold set to 0.99999
.......
........
Iteration: 37 Dual objective = 0.000000
Iteration: 38 Dual objective = 0.000000
Iteration: 39 Dual objective = 0.000000
Iteration: 40 Dual objective = 0.000000
Dual simplex solved model.
Maximum unscaled bound infeasibility = 0.846065.
Dual simplex - Optimal: Objective = 0.0000000000e+00
Solution time = 1.03 sec. Iterations = 62 (0)
Deterministic time = 709.00 ticks (688.03 ticks/sec)
THANK YOU VERY MUCH FOR YOUR HELP !!
Zak,
#CPLEXOptimizers#DecisionOptimization