An Approach to Robust Decision Making In Multidisciplinary Selection Problems Under Uncertainty

In this paper, the problem of choosing from a set of design alternatives based upon multiple, conflicting and uncertain criteria is investigated. Multiple attributes can arise when different disciplines contribute to the design of a product or process. The Overlap Measure Method developed in this paper models two sources of uncertainties – imprecise attribute values provided to the decision maker from the various disciplines and inabilities of the decision-maker to specify an exact desirable attribute level. Additionally, this method also provides the necessary steps to mitigate the effects of these sources of uncertainties using the Overlap Measure metric. The Overlap Measure Method can be applied to any theoretically sound multiattribute decision making method and in this paper is applied to the Hypothetical Equivalents and Inequivalents Method. The Overlap Measure Method also includes a sub-routine that ensures that the winning alternative is insensitive to changes in the relative importances of the different disciplines.