See "Diversity Maximization Approach for Multiobjective Optimization," 
Michael Masin and Yossi Bukchin, Operations Research March/April 2008
56:411-424

Abstract:
One of the most common approaches for multiobjective optimization is to generate
the whole or partial efficient frontier and then decide about the preferred 
solution in a higher-level decision-making process. In this paper, a new method 
for generating the efficient frontier for multiobjective problems is developed, 
called the diversity maximization approach (DMA). This approach is capable of 
solving mixed-integer and combinatorial problems. The DMA finds Pareto optimal 
solutions by maximizing a proposed diversity measure and guarantees generating 
the complete set of efficient points. Given a subset of the efficient frontier, 
DMA finds the next Pareto optimal solution which, combined with the existing 
ones, yields the most diversified subset of efficient points. This solution is 
defined as the most diverse solution. In fact, it aims to maximize the distance 
between the new efficient point and the closest point in the given subset of the 
efficient frontier. The proposed approach can be applied to any problem that 
can be solved for the single-objective case. We can use the DMA by solving 
directly a modified version of the mixed-integer programming (MIP) formulation 
of the multiobjective problem. In this case, the Pareto optimal solutions are 
found sequentially in an iterative way. Consequently, as we terminate the 
procedure before completion, a partial efficient frontier is available. 
The diversity measure assures that in every stage of the procedure, the 
partial efficient frontier is well diversified. This partial efficient frontier 
can be perceived as a filtered set of the complete efficient frontier and 
can be used by the decision maker in case the complete efficient frontier 
contains too many points. An additional way of using DMA is by incorporating 
it in a problem oriented branch-and-bound algorithm. Detailed examples of 
both approaches are given. 
