Uncertainties play a dominant role in the design and optimization of structures and infrastructures. In optimum design of structural systems due to variations of the material, manufacturing variations, variations of the external loads and modelling uncertainty, the parameters of a structure, a structural system and its environment are not given, fi

Yannis Tsompanakis, Nikos D. Lagaros, Manolis Papadrakakis

A. Reliability-based design optimization (RBDO) 1: Principles of reliability-based design optimization; 2: Reliability-based optimization of engineering structures; 3: Efficient approaches for system reliability-based design optimization; 4: Nondeterministic formulations of analytical target cascading for decomposition-based design optimization under uncertainty; 5: Design optimization of stochastic dynamic systems by algebraic reduced order models; 6: Stochastic system design optimization using stochastic simulation; 7: Numerical and semi-numerical methods for reliability-based design optimization; 8: Advances in solution methods for reliability-based design optimization; 9: Non-probabilistic design optimization with insufficient data using possibility and evidence theories; 10: Reliability analysis and reliability based design optimization using moment methods; 11: A decoupled approach to reliability based topology optimization for structural synthesis; 12: Sample average approximations in reliability-based structural optimization: Theory and applications; 13: Cost-benefit optimization for maintained structures; 14: A Reliability-Based Maintenance Optimization Methodoloy; 15: Overview of reliability analysis and design capabilities in DAKOTA with Application to Shape Optimization of MEMS. Part B. Robust design optimization (RDO) 16: Structural robustness and its relationship to reliability; 17: Maximum Robustness Design of Trusses via Semidefinite Programming; 18: A Taylor expansion approach to the design optimization of structures with randomness; 19: Info-gap robust design of passively controlled structures with load and model uncertainties; 20: Genetic algorithms and structural design using convex models of uncertainty; 21: Metamodel-based computing techniques for solving structural optimization problems considering uncertainties.