## 1 Introduction  
Ultra-wideband (UWB) antennas belong to the key components of modern location and tracking systems capable of providing centimeter-level accuracy [1; 2; 3; 4; 5; 6]. For the mentioned services, the radiators may find application not only to data exchange, but also as energy harvesting devices that provide the necessary power for sensors [7; 8; 9; 10]. A variety of application scenarios for tracking and location devices impose a range of potential requirements on antenna performance (in terms of field and electrical properties), as well as its dimensions (small footprint or specific shape) [11; 12; 13; 14; 15]. Consequently, a coherent system often comprises a range of antenna solutions. The development of radiators for UWB applications is widely covered in the available literature [16; 17; 18; 19; 20; 21; 22; 23; 24]. Conventional design solutions include a range of planar components, such as monopoles [17; 18] or dipoles [19; 20] as well as volumetric structures [21; 22]. Other antennas implement non-standard features that permit performance enhancement by excluding or including specific frequency bands [18; 23] or implementing composite topologies to achieve multiple-input multiple-output capability [24; 25]. Although the discussed antennas are characterized by varying dimensions or performance, their geometries stem from the mentioned basic topologies [16; 17; 18; 19; 20; 21; 22; 23; 24]. Consequently, enhanced functionality of the latter is often achieved through the introduction of specific geometry abbreviations (e.g., slots [23], stubs [24], perforations [11], or combinations thereof [16]). The modifications are predominantly introduced as a result of manual or semi-manual development, realized in a trial-and-error manner and oriented toward balancing the complexity and performance or size of the radiator [23; 24]. Other approaches to the generation of an antenna structure involve representation of its geometry using a set of characteristic points interconnected by lines or appropriately defined curves [26; 27; 28; 29; 30]. Alternatively, the topology can be defined using a binary matrix (often with overlapping components with variable dimensions) [31; 32; 33; 34], where zeros and ones correspond to the areas with etched or continuous metallization [32]. Contrary to conventional radiators, antenna topologies described using generic models are predominantly determined using optimization methods [35; 36; 37; 38; 39]. Notwithstanding, the applicability of numerical algorithms to the generation of unconventional geometries is often demonstrated based on relatively simple, single-objective problems [28; 29]. Furthermore, the optimization of generic models is normally undertaken using population-based routines (e.g., particle swarm optimization, genetic algorithms, or ant colony methods), which require thousands of evaluations to obtain the final solution [31; 35; 38; 40]. To put that into perspective, in [41], the particle swarm algorithm required a total of 248 EM simulations to solve a set of 12 problems represented using only one input parameter. In [42], the same method required over 1400 model evaluations to find an optimal design of frequency selective surface represented using three adjustable variables. Due to the high evaluation cost (being in the order of minutes to hours), the application of conventional, population-based routines for the EM-driven optimization of antennas defined using generic models is impractical from a computational standpoint. The design of modern antennas is a multi-objective (MO) problem, where a set of performance or geometry requirements is to be simultaneously fulfilled [38; 43; 44]. Conventional approaches to MO tasks involve conversion of the performance requirements into a single-objective function using aggregation techniques, penalty components, or design constraints [35; 39; 43]. The design task, formulated in this manner, can be solved using conventional single-objective routines [35; 43].