  In this work, we consider multiobjective optimization problems with both
bound constraints on the variables and general nonlinear constraints, where
objective and constraint function values can only be obtained by querying a
black box. Furthermore, we consider the case where a subset of the variables
can only take integer values. We propose a new linesearch-based solution method
and show that it converges to a set of stationary points for the problem. For
what concerns the continuous variables, we employ a strategy for the estimation
of the Pareto frontier recently proposed in the literature and which takes
advantage of dense sequences of search directions. The subset of variables that
must assume discrete values are dealt with using primitive directions
appropriately modified to take into account the presence of more than one
objective functions. Numerical results obtained with the proposed method on a
set of test problems and comparison with other solution methods show the
viability and efficiency of the proposed approach.
