Active Robust Optimization: Optimizing for Robustness of Changeable Products

This book presents a novel framework, known as Active Robust Optimization, which provides the tools for evaluating, comparing and optimizing changeable products. Since any product that can change its configuration during normal operation may be considered a changeable product, the framework is widely applicable. Further, the methodology enables designers to use adaptability to deal with uncertainties and so avoid over-conservative designs.

Offering a comprehensive overview of the framework, including its unique features, such as its ability to optimally respond to uncertain situations, the book also defines a new class of optimization problem and examines the effects of changes in various parameters on their solution. Lastly, it discusses innovative approaches for solving the problem and demonstrates these with two examples from different fields in engineering design: optimization of an optical table and optimization of a gearbox.

Explains how the readers' preferences and environmental factors can affect the final configuration of manufactured products Provides novel tools for the evaluation and optimization of reconfigurable products Develops unique solutions to optimizing automobile powertrains and control architecture

Autorentext

On completing his Ph.D., Dr. Shaul Solomon took up a position as lecturer at ORT Braude College, at the School of Mechanical Engineering. During his undergraduate mechanical engineering studies, he was awarded the Excellence Programme Scholarship at ORT Braude College, and made the President's List every semester. While studying for his doctorate, he received the Ph.D. Studentship Award, and was awarded the Kenneth Lindsay Scholarship for postgraduate studies. In 2012, he took part in the Marie Curie International Research Staff Exchange Scheme. He has already published five journal papers and presented his work at leading international conferences in the field of optimization, with plans to publish more work in the immediate future.

Inhalt

Introduction.- Background.- Active Robust Optimization.- Active Robust Multi-Objective Optimization.- Case Studies.- Conclusions.- Appendix: Calculation of the q+ Indicator.