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- W4328005928 abstract "Scheduling is a common decision-making process that plays a vital role in many manufacturing systems and information processing environments. Usually, all jobs in a scheduling problem need to be dispatched, and the objective function is related to the state after all jobs are completed. However, in order to balance the contradiction between the cost and the performance, many practice scenarios no longer require processing all jobs. The scheduling problem that only considers the completion of part jobs is referred to as percentile scheduling problem. In this work, we pave the way for it. We study and theoretically analyze the two percentile scheduling model of the multi-parallel machine environment, considering there is a release time or not. We propose an algorithm with a guaranteed approximation ratio for the model without release time to reduce our problem to the counterpart in the classical scheduling model. For the model with release time, an algorithm named CONVERT is designed, which combined with SRPT can produce a scheduling sequence with an approximation ratio of 6." @default.
- W4328005928 created "2023-03-22" @default.
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- W4328005928 date "2022-08-01" @default.
- W4328005928 modified "2023-10-16" @default.
- W4328005928 title "Percentile Optimization Based on Classical Parallel Machine Scheduling Model" @default.
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- W4328005928 doi "https://doi.org/10.1109/bigcom57025.2022.00020" @default.
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