Peak Shaving through Resource Buffering
Approximation and Online Algorithms
Saving energy for (and from) a sunny day: lowering peak demands with batteries
INFOCOM'09 Proceedings of the 28th IEEE international conference on Computer Communications Workshops
When to reap and when to sow - lowering peak usage with realistic batteries
WEA'08 Proceedings of the 7th international conference on Experimental algorithms
Multiindex optimal production planning problems
Automation and Remote Control
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We consider a very general online scheduling problem with an objective to minimize the maximum level of resource allocated. We find a simple characterization of an optimal deterministic online algorithm. We develop further results for the two, more specific problems of single resource scheduling and hierarchical line balancing. We determine how to compute optimal online algorithms for both problems using linear programming and integer programming, respectively. We show that randomized algorithms can outperform deterministic algorithms, but only if the amount of work done is a nonconcave function of resource allocation.