Our framework gives algorithms with the best or only-known competitive ratios for the concurrent open shop, coflow, and concurrent cluster models. We illustrate multiple applications of this method that yield improved competitive ratios.
19 permute 3 Offline#
Our framework uses two offline approximation algorithms-one for the simpler problem of scheduling without release times, and another for the minimum unscheduled weight problem-to create an online algorithm with provably good competitive ratios.
19 permute 3 how to#
, who show how to convert an offline approximation to an online scheme. The framework is inspired by the work of Hall et al. and use it to achieve improved competitive ratios for these same problems.ĪB - In this paper, we introduce a new online scheduling framework for minimizing total weighted completion time in a general setting. We also introduce a randomized variant of our framework based on the ideas of Chakrabarti et al. N2 - In this paper, we introduce a new online scheduling framework for minimizing total weighted completion time in a general setting. © Springer International Publishing AG, part of Springer Nature 2018.
We would also like to thank An Zhu and Google for their support, and the LILAC program at Bryn Mawr College. We would also like to thank An Zhu and Google for their support, and the LILAC program at Bryn Mawr CollegeĪll authors performed this work at the University of Maryland, College Park, under the support of NSF REU Grant CNS 156019. All authors performed this work at the University of Maryland, College Park, under the support of NSF REU Grant CNS 156019. We would like to thank Sungjin Im and Clifford Stein for directing us to, and William Gasarch for organizing the REU program. T2 - 13th International Symposium on Latin American Theoretical Informatics, LATIN 2018
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