Robust stochastic optimisation methods seek decision rules that perform reliably under both inherent randomness and ambiguity in probability models. Combining classical stochastic programming—where ...
Filled function methods constitute a class of deterministic global optimisation techniques designed to overcome the proliferation of local minima in complex, multimodal landscapes. By constructing an ...