Trading on infeasibility by exploiting constraint’s criticality through multi-objectivization: A system design perspective

Preferences are ubiquitous in real life - many problems are over-constrained and would not be solvable if we insist that all our requirements are strictly met. This paper portrays 'constraints' in an unconventional perspective, based on the realization that in order to truly maximize/minimize objective function(s), one has to optimize the feasible set. On a broader level, this paper acknowledges the need to move from 'optimizing the given', towards 'designing the optimal'. Here, the constraints are treated as objectives over and above the stated objective(s) and no other restrictions are used to 'constrain' the search space. We then evaluate this enhanced set of objectives, in terms of their criticality or redundancy. To this effect, we utilize our earlier proposed dimensionality reduction procedures to obtain a minimal set of objectives, which would characterize the original system with reasonable accuracy (from dimensionality reduction perspective) but with enhanced effectiveness (from a 'system design' perspective).