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I have a MIP which I know the solution almost for certain. I want to use gurobi to prove that the true solution (even if it is not the one i provide) shall not lie more than 0.5% deviated from the solution I gave. I believe that simply keep cutting without branching would possibly save much more time. Do you know a way that I could simply do cutting without branching in gurobi? thank you:D Here's the code performance:

Changed value of parameter LogFile to 
   Prev: gurobi.log   Default:

Changed value of parameter MIPFocus to 3
   Prev: 0   Min: 0   Max: 3   Default: 0

Changed value of parameter Cuts to 3
   Prev: -1   Min: -1   Max: 3   Default: -1

Optimize a model with 1794 rows, 673 columns and 4180 non zeros

Found heuristic solution: objective -22.8549

Presolve removed 18 rows and 17 columns

Presolve time: 0.01s

Presolved: 1776 rows, 656 columns, 4464 nonzeros

Loaded MIP start with objective -342.641

Variable types: 592 continuous, 64 integer (64 binary)
Presolved: 1776 rows, 656 columns, 4464 nonzeros

Root relaxation: objective -6.775689e+02, 682 iterations, 0.02 seconds

    Nodes    |    Current Node    |     Objective Bounds      |     Work
 Expl Unexpl |  Obj  Depth IntInf | Incumbent    BestBd   Gap | It/Node Time

     0     0 -677.56892    0   64 -342.64109 -677.56892  97.7%     -    0s
     0     0 -666.45290    0   72 -342.64109 -666.45290  94.5%     -    0s
     0     0 -658.68050    0   72 -342.64109 -658.68050  92.2%     -    1s
     0     0 -540.92023    0   72 -342.64109 -540.92023  57.9%     -    3s
     0     0 -503.36031    0   72 -342.64109 -503.36031  46.9%     -    4s
     0     0 -485.13025    0   72 -342.64109 -485.13025  41.6%     -    6s
     0     0 -472.73790    0   72 -342.64109 -472.73790  38.0%     -    8s
     0     0 -461.23185    0   72 -342.64109 -461.23185  34.6%     -    9s
     0     0 -453.99476    0   72 -342.64109 -453.99476  32.5%     -   10s
     0     0 -452.23014    0   72 -342.64109 -452.23014  32.0%     -   10s
     0     3 -452.23014    0   72 -342.64109 -452.23014  32.0%     -   11s

   642   586 -397.07656   12   54 -342.64109 -429.76289  25.4%   120   15s

  1425  1290 -397.34606   11   60 -342.64109 -422.53417  23.3%   114   20s

  1716  1553 -382.83438   18   72 -342.64109 -420.42709  22.7%   111   25s

  1727  1560 -376.17473   16   72 -342.64109 -420.42709  22.7%   110   30s

  1733  1564 -410.28764   10   72 -342.64109 -420.42709  22.7%   110   35s

  1744  1571 -382.83438   18   72 -342.64109 -420.42709  22.7%   109   40s

  1750  1577 -412.59771   12   69 -342.64109 -416.84728  21.7%   113   45s

  1817  1602 -380.32997   19   60 -342.64109 -404.73090  18.1%   120   50s

  2618  2045 -375.99924   18   62 -342.64109 -391.32863  14.2%   126   55s

  3159  2315 -369.40052   22   59 -342.64109 -386.33088  12.8%   127   60s

  3808  2595 -362.27693   20   60 -342.64109 -382.29310  11.6%   127   65s

  4503  2903 -350.90325   24   54 -342.64109 -379.52932  10.8%   126   71s

  4895  3078 -349.90847   23   55 -342.64109 -378.33598  10.4%   126   78s

  5339  3242 -363.26836   21   59 -342.64109 -376.77299  10.0%   126   80s

  6421  3664 -366.32746   21   56 -342.64109 -374.20072  9.21%   126   85s

  7560  4450 -357.93456   21   59 -342.64109 -371.61876  8.46%   126   90s

  8849  5297 -355.57657   21   59 -342.64109 -369.33074  7.79%   125   95s

 10004  6042 -357.02223   24   55 -342.64109 -367.63772  7.30%   124  100s

 11274  6819 -352.14570   23   55 -342.64109 -365.95440  6.80%   122  105s

 12362  7437 -357.95155   22   55 -342.64109 -364.73335  6.45%   122  110s

 13134  7882 -352.18831   25   47 -342.64109 -363.91508  6.21%   121  115s

....

asked 18 Jul '14, 12:25

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Chivalry
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Asked: 18 Jul '14, 12:25

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Last updated: 18 Jul '14, 12:25

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