The optimisation of gas networks has emerged as a critical field in energy systems engineering, incorporating advanced nonlinear programming techniques to address the increasing complexity of gas ...

We present a novel method for deriving tight Monte Carlo confidence intervals for solutions of stochastic dynamic programming equations. Taking some approximate solution to the equation as an input, ...

Dynamic programming algorithms are a good place to start understanding what's really going on inside computational biology software. The heart of many well-known programs is a dynamic programming ...