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.

翻译：在需求区包装问题(DSP)中,我们得到一个时间间隔和一系列任务,每个任务都有处理时间和对特定资源(例如电力、计算能力等)的需求。一个可行的解决办法是在所述时间间隔内制定任务时间表。我们的目标是尽量减少高峰资源消耗,即在任何时间点执行的任务的最大总需求。众所周知,DSP难以达到大约低于3/2系数的NP,而相关问题的标准技术意味着(Polomial-time)2(约合时间)2(约合时间)2。我们的主要结果就是为任何恒定eps>0计算一个(5/3+eps)-协调算法。我们还为一些相关的特殊案例实现最佳近似系数。