  In this paper, the truncated Euler-Maruyama (EM) method is employed together
with the Multi-level Monte Carlo (MLMC) method to approximate the expectations
of functions of solutions to stochastic differential equations (SDEs). The
convergence rate and the computational cost of the approximations using the
truncated EM method with the MLMC method are proved when the coefficients of
SDEs fulfill the local Lipschitz and Khasminskii-type conditions. Numerical
examples are given to demonstrate the theoretical results.
