Multi-objective vs Stochastic!

Hi everyone, 

Suppose a model is LP. However all decision variables are BINARY since
the problem structure does impose that.

It is also a multi-objective one since we have several conflicting
objectives (criteria). That means we need to generate Pareto solutions
by varying the objective weights, and Pareto frontiers by performing
sensitivity and scenario analysis.

If uncertainty is to be considered and Monte Carlo or Stochastic is to
be used.

Question: Is there a need to do simulation/stochastic since many (most
or all) of the solutions/frontiers obtained from the sensitivity and
scenario analysis would/could be the same as the ones obtained from
simulation/stochastic?

What do you think?

Mike