mirror of https://github.com/ANL-CEEESA/RELOG.git
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Gurobi Optimizer version 9.0.0 build v9.0.0rc2 (linux64)
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[ Info: Reading s1.json...
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Optimize a model with 124 rows, 141 columns and 400 nonzeros
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[ Info: Building graph...
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Model fingerprint: 0x46af87f0
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[ Info: 2 time periods
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Variable types: 117 continuous, 24 integer (24 binary)
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[ Info: 6 process nodes
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Coefficient statistics:
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[ Info: 8 shipping nodes (plant)
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Matrix range [5e-02, 2e+04]
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[ Info: 10 shipping nodes (collection)
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Objective range [9e-01, 3e+03]
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[ Info: 38 arcs
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Bounds range [1e+00, 1e+08]
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[ Info: Building optimization model...
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RHS range [3e+01, 2e+04]
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[ Info: Optimizing MILP...
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Presolve removed 98 rows and 107 columns
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[ Info: Re-optimizing with integer variables fixed...
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Presolve time: 0.00s
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[ Info: Extracting solution...
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Presolved: 26 rows, 34 columns, 74 nonzeros
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Variable types: 28 continuous, 6 integer (6 binary)
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Root relaxation: objective 1.870636e+06, 10 iterations, 0.00 seconds
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Nodes | Current Node | Objective Bounds | Work
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Expl Unexpl | Obj Depth IntInf | Incumbent BestBd Gap | It/Node Time
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0 0 1870636.06 0 2 - 1870636.06 - - 0s
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H 0 0 1871178.9617 1870636.06 0.03% - 0s
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Explored 1 nodes (10 simplex iterations) in 0.00 seconds
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Thread count was 8 (of 80 available processors)
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Solution count 1: 1.87118e+06
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Optimal solution found (tolerance 1.00e-02)
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Best objective 1.871178961663e+06, best bound 1.870636062997e+06, gap 0.0290%
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Gurobi Optimizer version 9.0.0 build v9.0.0rc2 (linux64)
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Optimize a model with 124 rows, 141 columns and 400 nonzeros
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Model fingerprint: 0x133a97e7
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Coefficient statistics:
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Matrix range [5e-02, 2e+04]
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Objective range [9e-01, 3e+03]
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Bounds range [1e+00, 1e+08]
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RHS range [3e+01, 2e+04]
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Presolve removed 115 rows and 110 columns
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Presolve time: 0.00s
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Presolved: 9 rows, 31 columns, 94 nonzeros
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Iteration Objective Primal Inf. Dual Inf. Time
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0 1.0296026e+06 1.950922e+03 0.000000e+00 0s
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7 1.8711790e+06 0.000000e+00 0.000000e+00 0s
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Solved in 7 iterations and 0.00 seconds
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Optimal objective 1.871178962e+06
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Reading s1.json...
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Building graph...
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Building optimization model...
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Optimizing MILP...
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Re-optimizing with integer variables fixed...
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Extracting solution...
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