This paper presents a comprehensive approach to optimizing Local Area Network (LAN) architecture through the integration of Genetic Algorithms (GA) for dynamic routing and virtualization to enhance network performance, scalability, and security. With the exponential growth in data traffic due to advancements in IoT, cloud computing, and mobile applications, traditional static network configurations have become inadequate. This study addresses these limitations by proposing a modular architecture that incorporates a GA-based routing optimizer, virtual servers, and advanced security protocols. The proposed solution is validated through simulations using Cisco Packet Tracer, NetworkX, and Python, demonstrating significant improvements in network efficiency, reduced latency, and enhanced security measures. The results highlight the potential of adaptive, AI-driven network management solutions in modern enterprise environments, offering a scalable and flexible approach to meet the evolving demands of network infrastructure. This research contributes to the field of network engineering by showcasing the practical applications of genetic algorithms and virtualization in optimizing LAN performance and security.

Index Terms- Genetic Algorithms, Network Virtualization and Dynamic Routing Optimization