## 5 Conclusions  
In conclusion, the findings from this study underscore the effectiveness of using a lamination of \([\,0_{3}^{\text{W}}/0_{3}^{\text{UD}}/0_{2}^{\text{W}}/0_{3}^{\text{UD}}/0_{4}^ {\text{W}}/0_{3}^{\text{UD}}/0_{2}^{\text{W}}/0_{2}^{\text{CORE}}/0_{2}^{\text{ WV}}/0_{3}^{\text{UD}}/0_{4}^{\text{WV}}/0_{3}^{\text{WV}}/0_{2}^{\text{WV}}/0_{3}^{ \text{UD}}/0_{3}^{\text{WV}}]\), as shown in the table with all laminae oriented at \(0^{\circ}\), for achieving near-optimal performance balance in terms of structural strength and mechanical characteristics while minimizing mass. The significant reduction in vehicle mass demonstrated by a 41.66% or 12.36 kg decrease in the monocoque weight highlights the potential for substantial gains in efficiency and performance. Furthermore, the anticipated 16.83% reduction in the overall hybrid chassis' mass, 42.984 kg in contrast to the 35.752 kg, compared to a conventional tubular frame, suggests that alternative designs can offer considerable benefits. Researchers and engineers are encouraged to consider these findings when designing similar structures, as the approach outlined enhances performance and also offers insights into efficient mass reduction strategies. However, it is important to note that modifications to the lamina orientation may not yield significant improvements in the areas of torsional stiffness and structural robustness, as shown by the data of Tables 13 and 16 and Figures 21 and 22, while they may introduce complexity in the manufacturing process, due to difficulties in accurately positioning the laminate plies. Figure 21: Variation in the elastic moduli value per experiment scenario. The results derived from the optimization algorithm offer a valuable reference for future research on optimizing composite materials in structural engineering applications, as they provide critical insights into the methodology, underscore the need for further evaluation, and identify areas for subsequent investigation. In particular, comparative analyses between the selected genetic algorithm and alternative optimization techniques such as particle swarm optimization (P.S.O.) methods would help to assess the G.A. 's efficacy in identifying near-optimal designs using metrics related to performance, such as computational time and resource usage. Furthermore, employing robust statistical methods, given sufficient tools and data, could more thoroughly evaluate the advantages and limitations of various optimization criteria. Additionally, investigating combinations of materials with diverse mechanical properties may enhance structural performance and mitigate failure risks. Moreover, the effect of adopting a material with more core height should be researched and incorporated in future executions of optimization routines. Finally, incorporating material cost parameters or further optimization criteria into the algorithmal procedure could facilitate the development of enhanced designs that balance mechanical properties with reduced manufacturing costs. Conceptualization, I.T. and D.A.D. ; methodology, I.T., D.A.D., A.S. and E.E.T. ; software, I.T. ; validation, I.T. and D.A.D. ; formal analysis, I.T. and D.A.D. ; investigation, I.T. ; resources, I.T., A.S., D.A.D. and E.E.T. ; data curation, I.T. ; writing--original draft preparation, I.T. ; writing--review and editing, I.T., D.A.D., A.S. and E.E.T. ; visualization, I.T. ; supervision, D.A.D. and E.E.T. ; project administration, D.A.D. ; funding acquisition, D.A.D. All authors have read and agreed to the published version of the manuscript. This research received no external funding. **Institutional Review Board Statement:** Not applicable.