  In this paper we study time-dependent scheduling problems where activities
consume a resource with limited availability. Activity durations as well as
resource consumptions are assumed to be time-dependent and the resource can be
replenished between activities. Because of the interaction of time-dependent
activity durations and resource consumptions, scheduling policies based on
starting all activities as early as possible may fail due to unnecessarily high
resource consumptions. We propose a dynamic discretization discovery algorithm
that generates a partially time-expanded network during the search. We propose
preloading techniques allowing to significantly reduce the computational effort
if the approach is embedded in an iterative solution procedure that frequently
evaluates activity sequences that start with the same activities. We evaluate
our approaches on a case of routing a fleet of electric vehicles in which
vehicles can recharge batteries during the route.
