  Network science is increasingly being developed to get new insights about
behavior and properties of complex systems represented in terms of nodes and
interactions. One useful approach is investigating localization properties of
eigenvectors having diverse applications including disease-spreading phenomena
in underlying networks. In this work, we evolve an initial random network with
an edge rewiring optimization technique considering the inverse participation
ratio as a fitness function. The evolution process yields a network having
localized principal eigenvector. We analyze various properties of the optimized
networks and those obtained at the intermediate stage. Our investigations
reveal the existence of few special structural features of such optimized
networks including the presence of a set of edges which are necessary for the
localization, and rewiring only one of them leads to a complete delocalization
of the principal eigenvector. Our investigation reveals that PEV localization
is not a consequence of a single network property, and preferably requires
co-existence of various distinct structural as well as spectral features.
