The Hamiltonian completion problem is to find the minimal number of edges to add to a graph to make it Hamiltonian.
The problem is clearly NP-hard in the general case (since its solution gives an answer to the NP-complete problem of determining whether a given graph has a Hamiltonian cycle).
The associated decision problem of determining whether K edges can be added to a given graph to produce a Hamiltonian graph is NP-complete.
Moreover, Hamiltonian completion belongs to the APX complexity class, i.e., it is unlikely that efficient constant ratio approximation algorithms exist for this problem.
[6] Gamarnik et al. use a linear time algorithm for solving the problem on trees to study the asymptotic number of edges that must be added for sparse random graphs to make them Hamiltonian.