  Network Design problems typically ask for a minimum cost sub-network from a
given host network. This classical point-of-view assumes a central authority
enforcing the optimum solution. But how should networks be designed to cope
with selfish agents that own parts of the network? In this setting, agents will
deviate from a minimum cost network if this decreases their individual cost.
Hence, designed networks should be both efficient in terms of total cost and
stable in terms of the agents' willingness to accept the network.
  We study this novel type of Network Design problem by investigating the
creation of $(\beta,\gamma)$-networks, that are in $\beta$-approximate Nash
equilibrium and have a total cost of at most $\gamma$ times the optimal cost,
for the recently proposed Euclidean Generalized Network Creation Game by Bil\`o
et al. [SPAA 2019]. There, $n$ agents corresponding to points in Euclidean
space create costly edges among themselves to optimize their centrality in the
created network. Our main result is a simple $\mathcal{O}(n^2)$-time algorithm
that computes a $(\beta,\beta)$-network with low $\beta$ for any given set of
points. Moreover, on integer grid point sets or random point sets our algorithm
achieves a low constant $\beta$. Besides these results, we discuss a
generalization of our algorithm to instances with arbitrary, even non-metric,
edge lengths. Moreover, we show that no such positive results are possible when
focusing on either optimal networks or perfectly stable networks as in both
cases NP-hard problems arise, there exist instances with very unstable optimal
networks, and there are instances for perfectly stable networks with high total
cost. Along the way, we significantly improve several results from Bil\`o et
al. and we asymptotically resolve their conjecture about the Price of Anarchy
by providing a tight bound.
