  This paper describes the design of a safeguarding scheme for Anderson
acceleration to improve its practical performance and stability when used for
first-order optimisation methods. We show how the combination of a
non-expansiveness condition, conditioning constraints, and memory restarts
integrate well with solver algorithms that can be represented as fixed point
operators with dynamically varying parameters. The performance of the scheme is
demonstrated on seven different QP and SDP problem types, including more than
500 problems. The safeguarded Anderson acceleration scheme proposed in this
paper is implemented in the open-source ADMM-based conic solver COSMO.
