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It is discussed the convergence of a Douglas–Rachford type splitting algorithm for the infinite dimensional stochastic differential equation $$begin{aligned} dX+A(t)(X)dt=X,dW text{ in } (0,T); X(0)=x, end{aligned}$$where (A(t):Vrightarrow Vu0027) is a nonlinear, monotone, coercive and demicontinuous operator with sublinear growth and V is a real Hilbert with the dual (Vu0027). V is densely and continuously embedded in the Hilbert space H and W is an H-valued Wiener process. The general case of a maximal monotone operators (A(t):Hrightarrow H) is also investigated.

A splitting algorithm for stochastic partial differential equations driven by linear multiplicative noise