  In the Demand Strip Packing problem (DSP), we are given a time interval and a
collection of tasks, each characterized by a processing time and a demand for a
given resource (such as electricity, computational power, etc.). A feasible
solution consists of a schedule of the tasks within the mentioned time
interval. Our goal is to minimize the peak resource consumption, i.e. the
maximum total demand of tasks executed at any point in time.
  It is known that DSP is NP-hard to approximate below a factor 3/2, and
standard techniques for related problems imply a (polynomial-time)
2-approximation. Our main result is a (5/3+eps)-approximation algorithm for any
constant eps>0. We also achieve best-possible approximation factors for some
relevant special cases.
