World Scientific
Skip main navigation

Cookies Notification

We use cookies on this site to enhance your user experience. By continuing to browse the site, you consent to the use of our cookies. Learn More
×

System Upgrade on Tue, May 28th, 2024 at 2am (EDT)

Existing users will be able to log into the site and access content. However, E-commerce and registration of new users may not be available for up to 12 hours.
For online purchase, please visit us again. Contact us at customercare@wspc.com for any enquiries.

Chapter 7: Multi-Objective Antenna Optimization Using Surrogate Models

      https://doi.org/10.1142/9781786341488_0007Cited by:13 (Source: Crossref)
      Abstract:

      Nowadays, the most popular approaches for solving multi-objective optimization problems are population-based metaheuristics. Their important advantage is the ability of generating the entire representation of the Pareto front in a single run of the algorithm. Other advantages include simplicity and availability of numerous (and often reliable) implementations. A brief exposition of these methods was provided in Chapter 6. On the other hand, a serious disadvantage of population-based algorithms is their considerable computational complexity. In a typical multi-objective setup, a large population size is utilized (from a 100 to a few hundreds of individuals) so that the overall number of objective function evaluations during the optimization run might be as high as a few thousands to tens of thousands. This becomes a fundamental bottleneck when applying metaheuristics for multi-objective design of contemporary antenna structures. As explained in Chapter 2, reliable performance evaluation of antennas requires full-wave electromagnetic (EM) analysis. Such analysis may be quite expensive particularly for realistic models (e.g., including connectors and installation fixtures) with typical simulation times of several minutes to a few hours per design. Clearly, straightforward optimization of EM models using population-based algorithms might be prohibitive…