  The development of sophisticated experimental means to control nanoscale
systems has motivated efforts to design driving protocols which minimize the
energy dissipated to the environment. Computational models are a crucial tool
in this practical challenge. We describe a general method for sampling an
ensemble of finite-time, nonequilibrium protocols biased towards a low average
dissipation. We show that this scheme can be carried out very efficiently in
several limiting cases. As an application, we sample the ensemble of
low-dissipation protocols that invert the magnetization of a 2D Ising model and
explore how the diversity of the protocols varies in response to constraints on
the average dissipation. In this example, we find that there is a large set of
protocols with average dissipation close to the optimal value, which we argue
is a general phenomenon.
