## 1 Introduction
Meshless methods have proven to be a more accurate alternative to FEM in demanding non-linear topics, such as fracture and impact mechanics, where problems involve transient domain boundaries and meshing becomes a challenge. Unlike FEM, meshless methods utilise arbitrarily distributed nodes and approximate field functions based on an influence domain rather than elements. Additionally, the rule in FEM that elements cannot overlap does not apply to meshless methods--their influence domains can and should overlap [7]. Pioneering the application of meshless methods in computational mechanics was the Diffuse Element Method (DEM), developed by [PERSON] et al. [8]. This method leveraged the approximation functions of the Moving Least Squares (MLS), introduced by [PERSON] and [PERSON] [9], to construct the required approximations [10; 11]. [PERSON] et al. [12] further enhanced the DEM concept and established one of the most prominent and widely used meshless methods--the Element Free Galerkin Method (EFGM). Over time, additional methods emerged, including the Petrov-Galerkin Local Meshless Method (MLPG) by [13], the Finite Point Method (FPM) by [14], and the Finite Sphere Method (FSM) by [15]. While these methods have been successfully applied to various problems in computational mechanics, they all share limitations, primarily stemming from the use of approximation functions instead of interpolation functions. The Point Interpolation Method (PIM) offers an alternative, effectively addressing the challenge of directly imposing essential boundary conditions [16]. This is achieved by constructing shape functions with the Kronecker delta property, making them simpler compared with methods such as the EFGM. Later, PIM has been enhanced with the incorporation of radial basis functions, leading to the Radial Point Interpolation Method (RPIM) [7; 17]. Other efficient interpolation meshless methods were developed in parallel, such as the Natural Element Method (NEM) [18], the Meshless Finite Element Method (MFEM) [19], and the Natural Radial Element Method (NREM) [20]. These methods offer the advantage of potentially utilising FEM pre-processing workflows (allowing them to be integrated into most FEM software), which can help mitigate the generally higher computational cost associated with these mesh-dependent numerical techniques. Among these methods, RPIM stands out as the most popular and well-represented interpolating meshless approach in the research literature [7]. The objective of the present study is to employ a bio-inspired bi-evolutionary optimisation algorithm for a suspension control arm. The control arm design is based on the geometry of existent industry-standard suspension arms. In the field of automotive mechanical construction, product development heavily relies on design philosophies informed by engineers' empirical knowledge. By applying automated techniques to selectively remove material from specific stressed components, it becomes feasible to achieve designs that align with the manufacturer's requirements while significantly reducing mass. Additionally, recent literature indicates a preference for meshless methods, which not only serve as a viable alternative to FEM but also offer potential advantages [21; 22]. The paper begins with a review and brief explanation of the studied numerical method, the RPIM. Next, the numerical procedures of a traditional bi-evolutionary algorithm are examined. Additionally, a parallel is drawn between these procedures and the concept of bone remodelling. The article proceeds to conduct a numerical study. The optimisation algorithm is applied to the control arm. The topologies are designed using industry-standard philosophies for this specific component. A linear-static analysis follows, comparing the stiffness, specific stiffness, displacement, and maximum von Mises stress values among the different designed models. Finally, the last section summarises the findings and revisits the conclusions drawn throughout this numerical study.