In this paper, we design the first streaming algorithms for the problem of multitasking scheduling on parallel machines with shared processing. In one pass, our streaming approximation schemes can provide an approximate value of the optimal makespan. If the jobs can be read in two passes, the algorithm can find the schedule with the approximate value. This work not only provides an algorithmic big data solution for the studied problem, but also gives an insight into the design of streaming algorithms for other problems in the area of scheduling.
Fu, Bin, Yumei Huo, and Hairong Zhao. 2022. “Streaming Algorithms for Multitasking Scheduling with Shared Processing.” Discrete Applied Mathematics 320 (October): 346–55. https://doi.org/10.1016/j.dam.2022.06.019.
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Discrete Applied Mathematics
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