An Adapted Non-Dominated Sorting Genetic Algorithm III (NSGA-III) with Repair-based operator for solving Controller Placement problem in Software-Defined Wide Area Networks

Optimum controller placement in the presence of several conflicting objectives has received significant attention Software-Defined Wide Area Network (SD-WAN) deployment. Multi-objective evolutionary algorithms, like Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Particle Swamp Optimization (MOPSO), have proved helpful solving Controller Placement Problem (CPP) SD-WAN. However, these algorithms were associated with challenge scalability (when there are more than three objectives) for optimization Hence, this study proposed an adapted NSGA-III (A-NSGA-III) to resolve challenges NSGA-II MOPSO objectives. This developed introduced a repair-based operator into existing Mechanical Engineering based propose A-NSGA-III optimal The A-NSGA-III, subjected evaluation using datasets from Internet2 OS3E WAN topology six objective functions. Hypervolume indicator, Percentage Coefficient Variation (PCV), percentage difference Parallel Coordinate Plots (PCP) confirmed that exhibited high convergence diversification number function exceeded three). result solved was recommended over subject confirmation usage conditions.