Online scheduling with general cost functions
نویسندگان
چکیده
We consider a general online scheduling problem on a single machine with the objective of minimizing ∑ j wjg(Fj), where wj is the weight/importance of job Jj , Fj is the flow time of the job in the schedule, and g is an arbitrary non-decreasing cost function. Numerous natural scheduling objectives are special cases of this general objective. We show that the scheduling algorithm Highest Density First (HDF) is (2+ )-speedO(1)-competitive for all cost functions g simultaneously. We give lower bounds that show the HDF algorithm and this analysis are essentially optimal. Finally, we show scalable algorithms are achievable in some special cases.
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