Table 2 Computational cost of a generic nature-inspired algorithm for antennas of Fig. 1.
From: On nature-inspired design optimization of antenna structures using variable-resolution EM models
EM model setup | Computational cost of the optimization process (N = 10, kmax = 100) | ||||
|---|---|---|---|---|---|
Antenna of Fig. 1a (broadband monopole) | Antenna of Fig. 1b (dual-band dipole) | ||||
Execution time (h) | Savings w.r.t. high-fidelity-based algorithm (%) | Execution time (h) | Savings w.r.t. high-fidelity-based algorithm (%) | ||
High-fidelity (L = Lmax) | 132.1 | – | 25.6 | – | |
Variable resolution (cf. (4)) \(L(k) = L_{\min } + (L_{\max } - L_{\min } )\left[ {\frac{k}{{k_{\max } }}} \right]^{p}\) | p = 0.5 | 82.2 | 37.7 | 18.0 | 29.6 |
p = 1.0 | 57.0 | 56.8 | 14.5 | 43.5 | |
p = 2.0 | 37.7 | 71.5 | 11.4 | 55.4 | |
p = 3.0 | 29.6 | 77.6 | 10.0 | 60.8 | |
