Recently, 3D Frequency Selective Surface (FSS) designs have become popular due to their enhanced performance at oblique incidence angles as compared to planar designs. While planar FSS design has been successfully performed using discrete nature-inspired evolutionary optimization algorithms such as the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), these algorithms are not suited for the problem of 3D FSS design, due to the generation of non-contiguous structures, making manufacturing difficult. One alternative to these algorithms is the Ant Colony Optimization (ACO) technique, which guarantees contiguous segments are generated. However, traditional ACO methods require meanders to continue until they are trapped, potentially generating a PEC unit cell. In this paper, a Multi-Objective Lazy Ant Colony Optimization (MOLACO) algorithm will be applied to the problem of FSS design. The introduction of lazy ants allows exploration of solutions previously inaccessible by traditional implementations of ACO. Simulated results will show that it is well suited to the problem of 3D FSS design.