SOLUTION SPACE EXPLORATION IN MODEL-BASED REALIZATION OF ENGINEERED SYSTEMS

George Box a British mathematician and professor of statistics wrote that "essentially, all models are wrong, but some are useful." In keeping with George Box's observation we suggest that in the model-based realization of complex systems, the decision maker must be able to work constructively with decision models of varying fidelity, completeness and accuracy in order to make defendable decisions under uncertainty. The models, and the search algorithms that use these models, will never be perfect and the inherent inaccuracy and incompleteness of analysis models and solvers manifest as uncertainties in the projected outcomes. Therefore, a significant and desirable step in any model-based application is to find stable and robust solutions in which variation of the (input) variables and parameters within manageable tolerances has the minimum effect on delivering favorable, system performance. In this paper we present a method for visualizing and exploring the solution space using the compromise Decision Support Problem (cDSP) as a decision model to aid a decision maker in finding these stable and robust solutions. The efficacy of the method is illustrated using the design of a shell and tube heat exchanger as an example. The method is generalizable to other decision constructs. Our emphasis is on the method rather than the results per se.