Networks are a widely used type of abstraction for complex data. Optimization of different quantitative objectives on networks often plays a crucial role in network science, not only when a practical solution is needed, but also for a general understanding of structural and statistical features of networks. We present multiscale approaches for two problems: optimal response to epidemics, and network generation. Both approaches are inspired by AMG scheme reinforced by the algebraic distance connectivity strength.