Robustness is the ability to survive unforeseen circumstances without undue damage or loss of function. It has become a requirement expressed in modern building codes, mostly without much advice as to how it can be achieved. Engineering has developed some approaches based on traditional practice as well as recent insight. However, knowledge about robustness remains scattered and ambiguous, making it difficult to apply to many specific cases. The author's attempt to collect and review elements, methods and strategies toward structural robustness, using a holistic, almost philosophical approach. This leads to a set of considerations to guide selection and implementation of measures in specific cases, followed by a collection of applications and examples from the authors practice. The world, engineering and construction are imperfect and not entirely predictable. Robustness provides a measure of structural safety beyond traditional codified design rules.

Robustness has recently become a popular term in structural and hydraulic engineering. However, the concept of 'robust design' or 'robustness' has no clear definition. The aim of this work was to find a definition for a robust system and to use this definition to search for an added value of robust design in structural engineering. The literature on robust design has been extensively studied to es-tablish a definition for a robust system. It was concluded that a robust system can be found by as-suming that the additional risk that arises due to discrepancies between the reality and the model, is smaller for a robust system than for a less robust system. When designing a system, it is however al-ways the priority to find a cost-optimal design alternative. In other words, economic optimization has priority over robustness. The reason for this it that robustness focuses on hazards for which no value of the risk can be defined, so that it cannot be quantified what may be spent on robustness. In this thesis, the meaning of a robust system was tested in several case studies. From the case studies it as investigated when and why robustness can be of added value.

The disciplines of science and engineering rely heavily on the forecasting of prospective constraints for concepts that have not yet been proven to exist, especially in areas such as artificial intelligence. Obtaining quality solutions to the problems presented becomes increasingly difficult due to the number of steps required to sift through the possible solutions, and the ability to solve such problems relies on the recognition of patterns and the categorization of data into specific sets. Predictive modeling and optimization methods allow unknown events to be categorized based on statistics and classifiers input by researchers. The Handbook of Research on Predictive Modeling and Optimization Methods in Science and Engineering is a critical reference source that provides comprehensive information on the use of optimization techniques and predictive models to solve real-life engineering and science problems. Through discussions on techniques such as robust design optimization, water level prediction, and the prediction of human actions, this publication identifies solutions to developing problems and new solutions for existing problems, making this publication a valuable resource for engineers, researchers, graduate students, and other professionals.

Throughout the past few years, there has been extensive research done on structural design in terms of optimization methods or problem formulation. But, much of this attention has been on the linear elastic structural behavior, under static loading condition. Such a focus has left researchers scratching their heads as it has led to vulnerable structural configurations. What researchers have left out of the equation is the element of seismic loading. It is essential for researchers to take this into account in order to develop earthquake resistant real-world structures. Structural Seismic Design Optimization and Earthquake Engineering: Formulations and Applications focuses on the research around earthquake engineering, in particular, the field of implementation of optimization algorithms in earthquake engineering problems. Topics discussed within this book include, but are not limited to, simulation issues for the accurate prediction of the seismic response of structures, design optimization procedures, soft computing applications, and other important advancements in seismic analysis and design where optimization algorithms can be implemented. Readers will discover that this book provides relevant theoretical frameworks in order to enhance their learning on earthquake engineering as it deals with the latest research findings and their practical implementations, as well as new formulations and solutions.