# Wire-Grid and Sparse MoM Antennas: Past Evolution, Present Implementation, and Future Possibilities
## 3 Optimization
### MoM Antennas and GA  
MoM has proved to be the best option among a large number of numerical methods used in combination with one of the optimization methods to improve the matrix-filling procedure and reduce the solution time. Thus, there have been attempts to combine Gas and MoM, for example. In particular, the paper [142] describes the design of compact microwave filters using GA in combination with the 2.5D MoM. In addition, the paper [193] presents the results of applying well-known numerical simulation codes (NEC) and GA to design wire antennas with circular polarization and wide angular coverage. In both cases, the results obtained from GA optimization showed excellent performance for the chosen optimization parameters. The method of creating new shapes for resonant structures is presented in [194]. To analyze the tested structures, the full-wave method in the spectral domain was used. This method effectively uses GA to find new forms of resonant structures. Meanwhile, the authors of [195] demonstrated the possibility of creating new, fully dielectric waveguide grating filters using GA to optimize the dielectric material permittivity and placement of geometric boundaries that separate homogeneous regions. The work [196] describes a technique to effectively combine GA and MoM to design an integrated antenna. This technique was proposed earlier in [197], and it is based on using the direct Z-matrix transformations (DMM) for effective GA and MoM integration. Using DMM with GA/MoM significantly reduces the overall optimization time by eliminating several filling operations on the Z-matrix. As an extension of an effective numerical method based on the derivation of closed-form Green's functions and the analytical evaluation of MoM matrix elements, the authors of [198] use the gradient search and GA in combination with electromagnetic simulation methods to evaluate the potential of using this approach as a CAD tool. In the work [199], the application of optimization methods to design ultra-wideband antennas for multifunctional wireless devices is discussed. The antennas investigated in this work are monopoles with flat all-metal radiating elements. In [200], the authors presented a procedure to design broadband microwave radiation absorbers including frequency-selective surface (FSS) screens embedded in a dielectric media, using GA with binary coding or the so-called microgenetic algorithm (MGA). Such a variant of GA simultaneously and optimally selects the material in each layer, the thickness of each layer, the periodicity of the FSS screen in the X and Y directions, its placement in the dielectric composite material, and the FSS screen material. The MGA was proposed by [PERSON] [201]. This approach avoids premature convergence and can show faster convergence to the near-optimal region compared to the conventional GA for the multivariate multimodal problem [202]. In 2002, the authors of [203] developed a planar broadband antenna by combining GA and MoM. GA was used to optimize the shape of the metallization pattern in order to minimize the return loss in a selected frequency range, while MoM was used to estimate the return loss. Further, the authors of [204] have successfully used the multistructure method of moments (MSMoM) presented in [93] to design printed antennas. The main advantage of MSMoM is that it provides a way to organize calculations, which is especially suitable for an iterative optimization procedure. In a classical electromagnetic simulation tool, the computation takes place within an optimization loop, so a new simulation procedure is required for each new structure. Thus, the simulation time increases if multiple structures need to be analyzed. By itself, MSMoM is not a fast solver since it does not reduce the computation time for a single simulation. The initial idea behind MSMoM is to simultaneously analyze multiple structures, parts of which are slightly different, with a single simulation.