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Investigating the Recoverable Robust Single Machine Scheduling Problem Under Interval Uncertainty

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Investigating the Recoverable Robust Single Machine Scheduling Problem Under Interval Uncertainty. / Bold, Matthew; Goerigk, Marc.
In: Discrete Applied Mathematics, Vol. 313, 31.05.2022, p. 99-114.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Bold, M & Goerigk, M 2022, 'Investigating the Recoverable Robust Single Machine Scheduling Problem Under Interval Uncertainty', Discrete Applied Mathematics, vol. 313, pp. 99-114. https://doi.org/10.1016/j.dam.2022.02.005

APA

Bold, M., & Goerigk, M. (2022). Investigating the Recoverable Robust Single Machine Scheduling Problem Under Interval Uncertainty. Discrete Applied Mathematics, 313, 99-114. https://doi.org/10.1016/j.dam.2022.02.005

Vancouver

Bold M, Goerigk M. Investigating the Recoverable Robust Single Machine Scheduling Problem Under Interval Uncertainty. Discrete Applied Mathematics. 2022 May 31;313:99-114. Epub 2022 Mar 11. doi: 10.1016/j.dam.2022.02.005

Author

Bold, Matthew ; Goerigk, Marc. / Investigating the Recoverable Robust Single Machine Scheduling Problem Under Interval Uncertainty. In: Discrete Applied Mathematics. 2022 ; Vol. 313. pp. 99-114.

Bibtex

@article{6fe280bc0c144d4ea39807820d87b845,
title = "Investigating the Recoverable Robust Single Machine Scheduling Problem Under Interval Uncertainty",
abstract = "We investigate the recoverable robust single machine scheduling problem under interval uncertainty. In this setting, jobs have first-stage processing times p and second-stage processing times q and we aim to find a first-stage and second-stage schedule with a minimum combined sum of completion times, such that at least \Delta jobs share the same position in both schedules.We provide positive complexity results for some important special cases of this problem, as well as derive a 2-approximation algorithm to the full problem. Computational experiments examine the performance of an exact mixed-integer programming formulation and the approximation algorithm, and demonstrate the strength of a proposed polynomial time greedy heuristic.",
keywords = "Scheduling, Optimisation under uncertainty, Recoverable robustness",
author = "Matthew Bold and Marc Goerigk",
year = "2022",
month = may,
day = "31",
doi = "10.1016/j.dam.2022.02.005",
language = "English",
volume = "313",
pages = "99--114",
journal = "Discrete Applied Mathematics",
issn = "0166-218X",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Investigating the Recoverable Robust Single Machine Scheduling Problem Under Interval Uncertainty

AU - Bold, Matthew

AU - Goerigk, Marc

PY - 2022/5/31

Y1 - 2022/5/31

N2 - We investigate the recoverable robust single machine scheduling problem under interval uncertainty. In this setting, jobs have first-stage processing times p and second-stage processing times q and we aim to find a first-stage and second-stage schedule with a minimum combined sum of completion times, such that at least \Delta jobs share the same position in both schedules.We provide positive complexity results for some important special cases of this problem, as well as derive a 2-approximation algorithm to the full problem. Computational experiments examine the performance of an exact mixed-integer programming formulation and the approximation algorithm, and demonstrate the strength of a proposed polynomial time greedy heuristic.

AB - We investigate the recoverable robust single machine scheduling problem under interval uncertainty. In this setting, jobs have first-stage processing times p and second-stage processing times q and we aim to find a first-stage and second-stage schedule with a minimum combined sum of completion times, such that at least \Delta jobs share the same position in both schedules.We provide positive complexity results for some important special cases of this problem, as well as derive a 2-approximation algorithm to the full problem. Computational experiments examine the performance of an exact mixed-integer programming formulation and the approximation algorithm, and demonstrate the strength of a proposed polynomial time greedy heuristic.

KW - Scheduling

KW - Optimisation under uncertainty

KW - Recoverable robustness

U2 - 10.1016/j.dam.2022.02.005

DO - 10.1016/j.dam.2022.02.005

M3 - Journal article

VL - 313

SP - 99

EP - 114

JO - Discrete Applied Mathematics

JF - Discrete Applied Mathematics

SN - 0166-218X

ER -