Lower and Upper Bounds for the General Multiobjective Optimization Problem

Searching over the Pareto front for the most preferred decision requires providing multiple Pareto optimal solutions to an instance of the general multiobjective optimization problem. This process, especially for large-scale problems can be time consuming and even can go over the resource (time, memory required) budget. In that case, lower and upper bounds are necessary to judge if the solutions derived thus far are acceptable approximations of the Pareto optimal ones. To this aim we provide lower and upper bounds for the general multiobjective optimization problem. This work generalizes our similar development valid for a special case.