A Proposal for Selecting a Pareto Solution with Desirable Properties

Decision making at both the strategic and operational levels in industrial and non-industrial organizations requires a compromise among economic, social, and environmental criteria. However, doing so on an empirical or expert sensitivity base is not recommendable. A robust approach is proposed to help the decision-maker in selecting a solution from the Pareto set, which is not a current practice. The approach involves applying various multi-criteria decision-making methods to select a Pareto-optimal solution with four key properties: low bias, high prediction quality, high resilience, and high robustness. These properties can be prioritized based on the decision-maker’s preferences. However, in order to take the decision maker’s uncertainty into account, various sets of weights are generated. Solution discrimination and validation are performed using the Sum of Ranking Differences technique, which makes it possible to prune Pareto solutions and identify the best one from a statistical point of view. A case study demonstrates the proposed approach’s usefulness, and it is apparent that changing the weight of Pareto-optimal solution properties, the most favorable solution, validated by the Sum of Ranking Differences technique, should change accordingly.