  A homotopy method for multi-objective optimization that produces uniformly
sampled Pareto fronts by construction is presented. While the algorithm is
general, of particular interest is application to simulation-based engineering
optimization problems where economy of function evaluations, smoothness of
result, and time-to-solution are critical. The presented algorithm achieves an
order of magnitude improvement over other geometrically motivated methods, like
Normal Boundary Intersection and Normal Constraint, with respect to solution
evenness for similar computational expense. Furthermore, the resulting
uniformity of solutions extends even to more difficult problems, such as those
appearing in common Evolutionary Algorithm test cases.
