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Reliability-based structural optimization (RBSO) considering probability distributions of random variables pertaining to load and strength parameters and satisfying system level reliability requirements is essential for optimization of practical structures. The computational and modeling complexities in RBSO using system level reliability constraints and the limitations of mathematical programming techniques are briefly discussed. The assessment of system reliability of real structures by the failure mode approach leads to numerous failure modes and requires complex modeling. A modified branch-and-bound algorithm is proposed to perform the system reliability assessment of discrete structures by failure-mode approach, and its computational efficiency in the optimization process is illustrated. Genetic algorithm based methodology for reliability-based configuration optimization of trusses is proposed, which satisfactorily addresses the computational and convergence problems. It is concluded that genetic algorithm based RBSO of trusses treating member sizes and configuration as design variables provides better optimal solutions for practical structures.
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