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Generalizing the Kawaguchi-Kyan bound to stochastic parallel machine scheduling
[article]

2018
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arXiv
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pre-print

Minimizing the sum of weighted completion times on $m$ identical parallel machines is one of the most important and classical scheduling problems. For the stochastic variant where processing times of jobs are random variables, M\"ohring, Schulz, and Uetz (1999) presented the first and still best known approximation result achieving, for arbitrarily many machines, performance ratio $1+\frac12(1+\Delta)$, where $\Delta$ is an upper bound on the squared coefficient of variation of the processing

arXiv:1801.01105v1
fatcat:ixb4aummhvgzravh5un3pyhb2u