Analog metamaterials (MMs) manipulate their effective medium parameters difficultly while its geometrical architecture is composed of hybrid compositions. However, the genic algorithm as a calculation analogue search algorithm seeking for optimal solution can be applied to artificial metamaterials architecture construction. Herein, a novel encoding strategy of metamaterial architecture construction utilizing multi-parameter seeking optimization was proposed. Binary encoding and decoding of the geometrical layer-thickness enables form final dimension based the objective fitness function. The algorithm iteration optimizes initial geometrical dielectric-layer thicknesses. Then, combining the optimizing initial parameter with composite multi-loops metal spatial distribution built final metamaterials in numerical analysis software. Based on this co-simulation disposition, the proposed metamaterial presents broadband features of 2.5GHz at the physical high-absorption to spatial wave over 80%. The proposed metamaterial presents low radar cross-sections, wide polarization insensitivity, and dynamical flexibility simultaneously. Moreover, a disposition of the proposed metamaterial loaded on a referenced antenna exhibits a well real applicated capability in radar cross-sections reduction for the physical passive equipment invisibility. Numerical simulation and experiment results in MMs properties of the absorption and flexibility show good agreements, suggesting the advantage of genic algorithm optimizations in co-simulation for metamaterials architecture construction which shows a good potential application in spatial complicated geometry forming.