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Erschienen in: Journal of Scheduling 2/2020

09.12.2019

An optimal online algorithm for scheduling with general machine cost functions

verfasst von: Islam Akaria, Leah Epstein

Erschienen in: Journal of Scheduling | Ausgabe 2/2020

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Abstract

We present two deterministic online algorithms for the problem of scheduling with a general machine cost function. In this problem, every machine has a cost that is given by a nonnegative cost function, and the objective function is the sum of makespan and the cost of the purchased machines. In previous work by Imreh, it was shown that no deterministic algorithm has competitive ratio below 2, and an algorithm whose competitive ratio does not exceed \((3+\sqrt{5})/2 \approx 2.618\) was presented. Our first algorithm imitates an optimal offline solution with respect to the number of machines used, and we show that its competitive ratio is exactly 2.5. Then, we modify our algorithm by imitating a preemptive optimal offline solution instead of a non-preemptive one. This leads to the design of a 2-competitive algorithm, which is the best possible.

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Fußnoten
1
We will not discuss how one can use an approximation scheme for converting it into a polynomial time algorithm as our other variant runs in polynomial time and its competitive ratio is smaller.
 
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Metadaten
Titel
An optimal online algorithm for scheduling with general machine cost functions
verfasst von
Islam Akaria
Leah Epstein
Publikationsdatum
09.12.2019
Verlag
Springer US
Erschienen in
Journal of Scheduling / Ausgabe 2/2020
Print ISSN: 1094-6136
Elektronische ISSN: 1099-1425
DOI
https://doi.org/10.1007/s10951-019-00629-3

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