Hi,
I have tested a MIP problem in branch-and-cut and got those results below.
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Reduced MIP has 33 rows, 132 columns, and 288 nonzeros.
Reduced MIP has 12 binaries, 0 generals, 0 SOSs, and 0 indicators.
Presolve time = 0.00 sec. (0.18 ticks)
Found incumbent of value 396952.000000 after 0.02 sec. (0.30 ticks)
Probing time = 0.00 sec. (0.04 ticks)
Tried aggregator 1 time.
MIP Presolve eliminated 22 rows and 88 columns.
Reduced MIP has 11 rows, 44 columns, and 96 nonzeros.
Reduced MIP has 4 binaries, 0 generals, 0 SOSs, and 0 indicators.
Presolve time = 0.00 sec. (0.07 ticks)
Probing time = 0.00 sec. (0.01 ticks)
Tried aggregator 1 time.
Detecting symmetries...
Reduced MIP has 11 rows, 44 columns, and 96 nonzeros.
Reduced MIP has 4 binaries, 0 generals, 0 SOSs, and 0 indicators.
Presolve time = 0.00 sec. (0.05 ticks)
Probing time = 0.00 sec. (0.01 ticks)
Clique table members: 1.
MIP emphasis: balance optimality and feasibility.
MIP search method: dynamic search.
Parallel mode: deterministic, using up to 16 threads.
Root relaxation solution time = 0.00 sec. (0.02 ticks)
Nodes Cuts/
Node Left Objective IInf Best Integer Best Bound ItCnt Gap
* 0+ 0 277443.0000 192888.0000 30.48%
0 0 272456.4088 2 277443.0000 272456.4088 7 1.80%
* 0+ 0 273984.0000 272456.4088 0.56%
* 0 0 integral 0 272484.0000 Fract: 1 8 0.00%
0 0 cutoff 272484.0000 272484.0000 8 0.00%
Elapsed time = 0.02 sec. (2.92 ticks, tree = 0.01 MB, solutions = 5)
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Now I am trying to get feasible solutions found at each iteration in python docplex for MIP problem.
Is it possible to obtain feasible solutions found at each iteration?
Also I would like to ask whether is it possible to get objective value at each node in branch-and-cut.
Thank you.
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Sangjeong Lee
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#DecisionOptimization