Another practicality associated with optimization problem is that a solution has to withstand multiple scenarios during its operation. Most existing studies optimize the worst scenario with the idea that if a solution is safe for the worst case, it is safe for all other cases. The flip side of this idea is that if there is an esoteric worst case which occurs with a small frequency and most frequent scenarios are milder than the worst case, then for most occasions the resulting solution is an over-design. In this work, we suggest an integrated approach which makes a good compromise of different scenarios. Multi-objective versions are also developed.