An optimization-based method for designing modular systems that traverse dynamic s-Pareto frontiers
The use of multiobjective optimization in identifying systems that account for changes in needs (preferences), operating environments, concepts, and analysis models over time is generally not explored. In terms ofidentifying sets of non-dominated designs, these changes result in the concept of dynamic Pareto frontiers, or dynamic s-Pareto frontiers in cases where sets of system concepts are being evaluated simultaneously over time. In a previous work by the authors, a 6-step optimization-based method was presented to identify systems that account for predicted changes in preferences by moving from one s-Pareto design to another through module addition. Addressing some of the limitations of this method, this paper presents an improved 5-step optimization-based method that builds on recent developments in multiobjective problem formulations of dynamic s-Pareto frontiers. In addition, recognizing the inherent uncertainty associated with predicting future needs or preferences and dynamic s-Pareto frontiers, the incorporation of uncertainty analysis in this improved method is also presented as an additional method improvement. Application of the presented method is illustrated through a modular plywood cart system for developing countries.
dynamic s-pareto frontiers multiobjective optimization modular system design pareto traversing