Latin supercube sampling for very high-dimensional simulations
ACM Transactions on Modeling and Computer Simulation (TOMACS) - Special issue on uniform random number generation
A combined reliability analysis approach with dimension reduction method and maximum entropy method
Structural and Multidisciplinary Optimization
A design optimization strategy for creating devices that traverse the Pareto frontier over time
Structural and Multidisciplinary Optimization
Pareto set analysis: local measures of objective coupling in multiobjective design optimization
Structural and Multidisciplinary Optimization
Structural and Multidisciplinary Optimization
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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.