CPX_STAT_MULTIOBJ_NON_OPTIMAL

All sub-problems solved during the solution of a multi-objective problem have been solved, but at least one of them has not been solved to optimality.

For a multi-objective MIP, CPLEX returns CPX_STAT_MULTIOBJ_NON_OPTIMAL in two cases. The first one arises when at least one of the MIP sub-problems could not be solved to optimality because a local work limit specified by the user (such, e.g., a deterministic time limit) was hit during the solution process, but all the MIP sub-problems were feasible. The second one arises when at least one of the MIP sub-problems was solved to optimality but with unscaled infeasibilities (that is, with solution status CPXMIP_OPTIMAL_INFEAS). In both cases, a primal feasible solution of the multi-objective MIP is available.

For a multi-objective LP, CPLEX returns CPX_STAT_MULTIOBJ_NON_OPTIMAL when it encountered some numeric difficulties during optimization, that is, when any of the LP-subproblems was solved with solution status CPX_STAT_OPTIMAL_INFEAS or CPX_STAT_NUM_BEST.

Query the individual sub-problem statuses for more information about the single sub-problems.