  This paper presents an adaptive multiple-shooting method to solve stochastic
multi-point boundary value problems. The heuristic to choose the shooting
points is based on separating the effects of drift and diffusion terms and
comparing the corresponding solution components with a pre-specified initial
approximation. Having obtained the mesh points, we solve the underlying
stochastic differential equation on each shooting interval with a first-order
strongly-convergent stochastic Runge-Kutta method. We illustrate the
effectiveness of this approach on 1-dimentional and 2-dimentional test problems
and compare our results with other non-adaptive alternative techniques proposed
in the literature.
