Uncertain programming: a unifying optimization theory in various uncertain environments
Applied Mathematics and Computation
Design of experiments: robust design: seeking the best of all possible worlds
Proceedings of the 32nd conference on Winter simulation
Simulation based operational analysis of future space transportation systems
Proceedings of the 32nd conference on Winter simulation
Simulation based design for a shipyard manufacturing process
Proceedings of the 32nd conference on Winter simulation
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Hierarchical design scenarios arise when the performance of large-scale, complex systems can be affected through the optimal design of several smaller functional units or subsystems. Monte Carlo simulation provides a useful technique to evaluate probabilistic uncertainty in customer-specified requirements, design variables, and environmental conditions while concurrently seeking to resolve conflicts among competing subsystems. This paper presents a framework for multidisciplinary simulation-based design optimization, and the framework is applied to the design of a Formula 1 racecar. The results indicate that the proposed hierarchical approach successfully identifies designs that are robust to the observed uncertainty.