Improving Optical Network Efficiency: A Comprehensive Approach for Power Optimisation, Blocking Probability Reduction, and Resource Management Using the Modified Genetic Algorithm

Optical networks require effective resource allocation in Dense Wavelength Division Multiplexing (DWDM) networks for optimizing performance metrics such as blocking probability(BP), power economy(PE), and resource utilization(RU). This study evaluates Modified Genetic Algorithm (MGA) by comparing its performance with principal techniques like 2R,3R and All-Optical Wavelength Conversion (AOWC). MGA is used to improve Routing and Wavelength Assignment (RWA), minimising BP and enhancing RU via optimised selection of algorithms. The 2R and 3R regeneration systems combat signal degradation, therefore enhancing performance efficiency by reducing accumulated noise. AOWC facilitates dynamic wavelength reassignment, mitigating congestion and enhancing spectrum efficiency. Simulation results demonstrate that MGA takes minimum time to attain a desirable balance among BP, RU, and PE, establishing it as the most efficient method for mitigating congestion in high-traffic optical networks. These findings highlight the importance of combining intelligent optimisation algorithms with signal regeneration techniques to improve the sustainability of WDM networks.