[Scip] Pricing performs apparently useless rounds in column-and-row generation approach

[Andreas Gebauer]

Hi all,

I'm working on a simultaneous column-and-row-generation approach.
When testing with various instances, SCIP behaves in a way I don't understand.

After adding new variables (with SCIPaddPricedVar) and constraints (with SCIPaddCons) in the ObjPricer redcost method, SCIP performs a LP-iteration (as it should be).
Sometimes, the next pricing round does not find solutions with negative reduced costs. 
Normally, the pricing should be aborted (delay flag is set to TRUE) but SCIP reruns the pricer with dual variables that differ from the last ones.
Now, solutions with negative reduced costs are found and the process continues normally.

I observed that this behaviour comes along with divergent numbers of vars and cols or cons and rows.
The best (and only) explanation I have is that there is something wrong with the way I add the constraints (or variables) in solving status.
Does anybody of you have an idea what a typical mistake might be?

Some display lines are attached at the end of the mail that hopefully make clear what the problem is about.

Best regards,
Andreas

1.Example:
 time | node  | left  |LP iter|LP it/n| mem |mdpt |frac |vars |cons |cols |rows |cuts |confs|strbr|  dualbound   | primalbound  |  gap   
  4.6s|     1 |     0 |   567 |     - |3523k|   0 |   0 |1017 | 977 |1017 | 952 |  92 |   0 |   0 | 2.304000e+02 | 2.314000e+02 |   0.43%
  4.6s|     1 |     0 |   567 |     - |3523k|   0 |   0 |1017 | 977 |1017 | 952 |  92 |   0 |   0 | 2.304000e+02 | 2.314000e+02 |   0.43%
[a pricing round is performed without adding new variables (since objective value of best pricing solution is 0)]
  4.7s|     1 |     0 |   616 |     - |3529k|   0 |   0 |1017 | 977 |1017 | 964 | 104 |   0 |   0 | 2.304000e+02 | 2.314000e+02 |   0.43%
  4.7s|     1 |     0 |   616 |     - |3529k|   0 |   0 |1017 | 977 |1017 | 964 | 104 |   0 |   0 | 2.304000e+02 | 2.314000e+02 |   0.43%
[now, new variables with negative reduced costs are found]


2.Example:
  0.1s|     1 |     0 |    13 |     - |1925k|   0 |   0 | 504 | 514 | 501 | 501 |   0 |   0 |   0 | 1.600000e+02 | 2.000000e+02 |  25.00%
[a pricing round is performed without adding new variables (since objective value of best pricing solution is 0)]
  0.1s|     1 |     0 |    15 |     - |1925k|   0 |   0 | 504 | 514 | 504 | 501 |   0 |   0 |   0 | 1.600000e+02 | 2.000000e+02 |  25.00%
[now, new variables with negative reduced costs are found]