I have a number of fairly large LP problems for which I just want to find any feasible solution. I've given these problems to GLPK, CLP and CPLEX "out of the box" (i.e. not specifying any parameters, just asking for the default behavior). Although all of them do find the feasible vectors that I desired, only CLP produces "nice" vectors. For instance one of the problems has 32768 variables divided into two sets of 16384. CLP produces a vector for which only 3 out of the 16384 variables in the first set are nonzero, and all the nonzero values for variables in the second set are 1.0 and all of the nonzero indices occur in consecutive chunks of 256. My question is what is the default solution strategy for CLP (and if anyone knows for GLPK and CPLEX). Clearly, by serendipity, CLP is finding some nice structure in my problem, so I'd like to uncover it.<br>
<br>Victor Miller<br><br>