Keywords: programmable metamaterials, hybrid lattice, stiffness–vibration trade-off, hyperbolic unit cell, genetic algorithm, fast design.

This conference short paper presents a numerical design route for programmable hyperbolic metamaterials formed by mixing chiral and achiral unit cells within a unified parametric family. A regular 5x4x3 lattice assembly is parameterized and converted into beam-based finite-element models for quasi-static compression, first-order modal analysis, and PSD-based random-vibration evaluation. Based on 21 randomly generated hybrid layouts with prescribed achiral fractions, the accessible performance space is quantified in terms of equivalent stiffness, first-order natural frequency, and acceleration root-mean-square (RMS). The results show that increasing the achiral fraction raises stiffness and modal frequency but aggravates the random-vibration response, revealing a pronounced stiffness-isolation trade-off. A binary genetic-algorithm framework is then used to optimize the unit-cell distribution for stiffness maximization, first-mode maximization, RMS minimization, and RMS minimization under a stiffness constraint. The optimized layouts indicate that stiffness- and frequency-driven objectives favor vertically continuous achiral load paths, whereas vibration-oriented objectives disrupt those paths and, under stiffness constraints, evolve toward layered compromise patterns. The study therefore provides a concise and reusable numerical route for programmable performance allocation in lattice support structures.

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