On the on-line maintenance scheduling problem

Fahimeh Shamsaei; Claudio Telha; Mathieu Van Vyve

doi:10.1007/s11590-017-1198-6

On the on-line maintenance scheduling problem

Fahimeh Shamsaei, Claudio Telha, Mathieu Van Vyve^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

A machine instantly serves requests but needs to undergo maintenance after serving a maximum of L requests. We want to maximize the number of requests served. In the on-line version, we prove that serving L requests before placing a maintenance is 0.5-competitive and is best possible for deterministic algorithms. We describe a 0.585-competitive randomized algorithm and show an upper bound of 2 L/ (3 L- 1). We also analyze the empirical performance of various on-line algorithms on specific arrival distributions.

Original language	English
Pages (from-to)	387-397
Number of pages	11
Journal	Optimization Letters
Volume	12
Issue number	2
DOIs	https://doi.org/10.1007/s11590-017-1198-6
State	Published - 1 Mar 2018
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2017, Springer-Verlag GmbH Germany.

Keywords

Competitive analysis
Maintenance scheduling
Randomized algorithms

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10.1007/s11590-017-1198-6

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N2 - A machine instantly serves requests but needs to undergo maintenance after serving a maximum of L requests. We want to maximize the number of requests served. In the on-line version, we prove that serving L requests before placing a maintenance is 0.5-competitive and is best possible for deterministic algorithms. We describe a 0.585-competitive randomized algorithm and show an upper bound of 2 L/ (3 L- 1). We also analyze the empirical performance of various on-line algorithms on specific arrival distributions.

AB - A machine instantly serves requests but needs to undergo maintenance after serving a maximum of L requests. We want to maximize the number of requests served. In the on-line version, we prove that serving L requests before placing a maintenance is 0.5-competitive and is best possible for deterministic algorithms. We describe a 0.585-competitive randomized algorithm and show an upper bound of 2 L/ (3 L- 1). We also analyze the empirical performance of various on-line algorithms on specific arrival distributions.

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KW - Maintenance scheduling

KW - Randomized algorithms

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On the on-line maintenance scheduling problem

Abstract

Bibliographical note

Keywords

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