Hi, I have an application that solves tens of million of tiny LPs coming from matrix games. On checking the kkt optimality conditions, there are a dozen cases where both the primal and dual solutions are incorrect, and about one hundred cases with low quality dual or primal feasibility. The LPs were scaled using the parameter "GLP_SF_AUTO". I'm hoping there is some way to fix these problem cases by re-solving the LP with different parameters. The problem cases generally seem to have multiple constraints that are identical; I suspect that this is the source of the problem.
I'm thinking that I might be able to fix this by enabling the presolver. For efficiency reasons, it seems to make sense to selectively enable the presolver for the LPs that don't satisfy the kkt optimality conditions? But quoting the manual -- "Presolving may be used when the problem instance is solved for the first time. However, on performing re-optimization the presolver should be disabled." This seems to imply that I shouldn't solve a problem with presolver disabled and then try to correct it by re-optimizing with the presolver. I.e. I should use the presolver on all instances. Is this right? Also, since the LPs are of the same size and are dense, I set up the LP once and then on successive LPs, change the matrix values and reload it. Does this qualify as a re-optimization where the presolver should be disabled? -- Glenn C. Rhoads _______________________________________________ Help-glpk mailing list [email protected] http://lists.gnu.org/mailman/listinfo/help-glpk
