This paper presents a methodology for reliability-based multi-objective design optimization (RBMODO) of automotive body components under impact scenario. Conflicting design requirements arise as one tries, for example, to minimize structural mass while maximizing energy absorption of an automotive rail section under structural and occupant safety related performance measure constraints. Because deterministic optimum designs obtained without taking uncertainty into account could lead to unreliable designs, a reliability-based approach to design optimization is preferable using a Reliability-based design optimization method. Uncertainty quantification is performed using two methods: reliability based approach and robustness based approach. The technique employed here treats multiple objective functions separately without combining them in any form. A decision-making criterion is subsequently invoked to select the “best” subset of solutions from the obtained non-dominated Pareto optimal solutions. The pareto optimal set obtained in case are compared and contrasted and observations made comparing reliability based approach vis-a`-vis robustness based approach. Deterministic, reliability-based and robustness based multi-objective optimization solutions are compared.

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