Abstract
The uncertainty of the engineering system increases with the growing complexity of the engineering system; therefore, the tolerance to the uncertainty is essential. In the design phase, the output performance should reach the design criterion, even under large variations of design parameters. The tolerance to design parameter variations may be measured by the size of a solution space in which the output performance is guaranteed to deliver the required performance. In order to decouple dimensions, a maximum solution hyperbox, expressed by intervals with respect to each design parameter, is sought. The proposed approach combines the metaheuristic algorithm with the DIRECT algorithm where the former is used to seek the maximum size of hyperbox, and the latter is used as a checking technique that guarantees the obtained hyperbox is indeed a solution hyperbox. There are three advantages of the proposed approach. First, it is a global search and has a considerable high possibility to produce the globally maximum solution hyperbox. Second, it can be used for both analytically known and black-box performance functions. Third, it guarantees that any point selected within the obtained hyperbox satisfies the performance criterion as long as the performance function is continuous. Furthermore, the proposed approach is illustrated by numerical examples and real examples of complex systems. Results show that the proposed approach outperforms the GHZ and CES-IA methods in the literature.
Highlights
With the rapid development of technology in recent years, the systems applied in various engineering areas such as electronics, communication, and networking have become more and more complex. e increasing complexity of the system provides a new source for the uncertainty
An innovative global approach that combines metaheuristic algorithms and the DIRECT algorithm is proposed to seek a maximum solution hyperbox. e metaheuristic algorithm is used to obtain a maximum hyperbox and the DIRECT algorithm is used as a checking technique to guarantee that the obtained hyperbox is a solution hyperbox
The sensitivity analysis (SA)-DIRECT and dCMA-evolution strategy (ES)-DIRECT methods are presented in detail. e results of studies on complex numerical examples and engineering cases have shown that these two methods have better performance than the GHZ and cellular evolutionary strategies (CES)-interval arithmetic (IA) methods
Summary
With the rapid development of technology in recent years, the systems applied in various engineering areas such as electronics, communication, and networking have become more and more complex. e increasing complexity of the system provides a new source for the uncertainty. With the rapid development of technology in recent years, the systems applied in various engineering areas such as electronics, communication, and networking have become more and more complex. E increasing complexity of the system provides a new source for the uncertainty. Uncertainty arises because some design parameters cannot yet be specified exactly or they may be changed over the course of development [1, 2]. Traditional optimization techniques seek an optimum in the design space. Without considering the uncertainty, the optimum design is frequently pushed to the constraint boundary of the design. This type of optimum design may be nonrobust and sensitive to parameter variabilities. Some authors even believe that optimization is just the opposite of robustness [3]
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call