- author = "Jennifer Rayno and Magdy Iskander and Marcelo kobayashi",
- journal = "IEEE Antennas and Wireless Propagation Letters",
- title = "Hybrid Genetic Programming with Accelerating Genetic Algorithm Optimizer for {3D} Metamaterial Design",
- year = "2016",
- volume = "15",
- pages = "1743--1746",
- month = "18 " # feb,
- keywords = "genetic algorithms, genetic programming, 3-D metamaterial synthesis, artificial magnetic conductor",
-
DOI = "
doi:10.1109/LAWP.2016.2531721",
- ISSN = "1536-1225",
- size = "4 pages",
- abstract = "The computational efficiency of existing genetic programming (GP) software is improved through the addition of parallelization and hybridization with a low-level optimiser. The low-level optimiser is implemented using genetic algorithm (GA), and two different versions of the developed hybrid GP program are presented. Timing and efficiency performance are discussed, which includes a method of making the original optimiser more than eight times faster. Efficiency results indicate that through the use of the optimiser, with sufficient variables included, significantly fewer (about quarter to half) GP generations are required to achieve working metamaterial designs. Two low frequency, broadband (225-450MHz) ground plane design examples, which are 25.3percent thinner than a previously published design covering the same frequency band, are included.",
-
notes = "Jennifer Rayno is with the Hawaii Center for Advanced
Communications (HCAC), University of Hawaii at Manoa,
Honolulu, HI 96822 USA
Also known as \cite{7412669}",
