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, fixed coefficients, but random variables with a certain probability distribution. The increasing necessity to solve complex problems in Structural Optimization, Structural Reliability and Probabilistic Mechanics, requires the development of new ideas, innovative methods and numerical tools for providing accurate numerical solutions in affordable computing times.

This book presents the latest findings on structural optimization considering uncertainties. It contains selected contributions dealing with the use of probabilistic methods for the optimal design of different types of structures and various considerations of uncertainties. The first part is focused on reliability-based design optimization and the second part on robust design optimization. Comprising twenty-one, self-contained chapters by prominent authors in the field, it forms a complete collection of state-of-the-art theoretical advances and applications in the fields of structural optimization, structural reliability, and probabilistic computational mechanics. It is recommended to researchers, engineers, and students in civil, mechanical, naval and aerospace engineering and to professionals working on complicated costs-effective design problems.

Part A. Robust design optimization (RDO)
A1. Basic aspects on RDO

• 1: Evaluation and Maximization of Robustness of Trusses by using Semidefinite Programming
  Yoshihiro Kanno and Izuru Takewaki.
• 2: A Taylor expansion approach to the design optimization of structures with randomness
  Ioannis Doltsinis, Zhan Kang.

A2. Theoretical advances on RDO

• 3: Cost-Benefit Optimization and Risk Acceptability for Maintained Structures
  R. Rackwitz and A. Joanni.
• 4: Efficient robust-design optimization involving dynamic reliability problems Alexandros A. Taflanidis and James L. Beck.
• 5: Robust design optimization using possibility theory
  Byeng Dong Youn.
• 6: Bridging the gap between robust and reliability-based design optimization with the saddlepoint expansion
  Jorge E. Hurtado.

A3. Application driven chapters on RDO

• 7: Info-gap robust design of passively controlled structures with load and model uncertainties
  Izuru Takewaki and Yakov Ben-Haim.
• 8: Efficient computing techniques for structural reliability-based robust design optimization Nikos D. Lagaros, Vaggelis Plevris, and Yiannis Tsompanakis.
  

Part B. Reliability-based design optimization (RBDO)
B1. Basic aspects on RBDO

• 9: Reliability-based structural optimization
  Alaa Chateauneuf.
• 10: Efficient approaches for system reliability-based design optimization
  Zissimos P. Mourelatos, Jinghong Liang and Efstratios Nikolaidis.

B2. Theoretical advancements and academicapplications of RBDO

• 11: Numerical and semi-numerical methods for reliability-based design optimization
  G. Kharmanda.
• 12: Non-probabilistic design optimization with insufficient data using possibility and evidence theories
  Zissimos P. Mourelatos and Jun Zhou.
• 13: Efficient stochastic methods in RBDO
  Alaa Chateauneuf.
• 14: Reliability analysis and reliability based design optimization using the moment method
  Byung Man Kwak, Sang Hoon Lee and Jae Sung Huh.
• 15: Analytical target cascading in optimal design of decomposed systems under uncertainty
  M. Kokkolaras and P.Y. Papalambros.
• 16: Reliability based topology optimization using the hybrid cellular automaton method
  Neal M. Patel, John E. Renaud, Harish Agarwal and Andres Tovar.
• 17: Sample average approximations in Reliability-based structural optimization: Theory and applications
  J.O. Royset, E. Polak.

B3. Application-driven chapters on RBDO

• 18: Design optimization of stochastic dynamic systems by algebraic reduced order models
  G. Weickum, M. Allen, K. Maute and D. Frangopol.
• 19: Reliability-based damage tolerance methodology
  Y-T. Wu.
  20: Overview of reliability analysis and design capabilities in DAKOTA with Application to Shape Optimization of MEMS
• M.S. Eldred, S.A. Mitchell, B. J. Bichon and B. M. Adams.