Optimization under ordinal scales: When is a greedy solution optimal?
Mathematical formulation of an optimization problem often depends on data
which can be measured in more than one acceptable way. If the conclusion
of optimality depends on the choice of measure, then we should question
whether it is meaningful to ask for an optimal solution. If a meaningful
optimal solution exists and the objective function depends on data
measured on an ordinal scale of measurement, then the greedy algorithm
will give such a solution for a wide range of objective functions. Copyright Physica-Verlag 1997