Comparison of different approaches to multistage lot sizing with uncertain demand

We study a new variant of the classical lot sizing problem with uncertain demand where neither planning horizon nor demands are known exactly. This situation arises in practice when customer arriving over time confirmed rather lately during transportation process. In terms planning, this setting necessitates rolling procedure overall multistage is dissolved into series coupled snapshot problems under uncertainty. Depending on available data and risk disposition, different approaches from online optimization, stochastic programming, robust optimization viable to model solve problems. evaluate impact selected methodology solution quality using methodology-agnostic framework for decision-making provide computational results within regarding types uncertainty, approaches, value information about upcoming demands.