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A faster exact method for solving the robust multi-mode resource-constrained project scheduling problem

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A faster exact method for solving the robust multi-mode resource-constrained project scheduling problem. / Bold, M.; Goerigk, M.
In: Operations Research Letters, Vol. 50, No. 5, 30.09.2022, p. 581-587.

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

Harvard

Bold, M & Goerigk, M 2022, 'A faster exact method for solving the robust multi-mode resource-constrained project scheduling problem', Operations Research Letters, vol. 50, no. 5, pp. 581-587. https://doi.org/10.1016/j.orl.2022.08.003

APA

Bold, M., & Goerigk, M. (2022). A faster exact method for solving the robust multi-mode resource-constrained project scheduling problem. Operations Research Letters, 50(5), 581-587. https://doi.org/10.1016/j.orl.2022.08.003

Vancouver

Bold M, Goerigk M. A faster exact method for solving the robust multi-mode resource-constrained project scheduling problem. Operations Research Letters. 2022 Sept 30;50(5):581-587. Epub 2022 Sept 13. doi: 10.1016/j.orl.2022.08.003

Author

Bold, M. ; Goerigk, M. / A faster exact method for solving the robust multi-mode resource-constrained project scheduling problem. In: Operations Research Letters. 2022 ; Vol. 50, No. 5. pp. 581-587.

Bibtex

@article{92cbb1a4283f47918baafa0d7354c6ec,
title = "A faster exact method for solving the robust multi-mode resource-constrained project scheduling problem",
abstract = "This paper presents a mixed-integer linear programming formulation for the multi-mode resource-constrained project scheduling problem with uncertain activity durations. We consider a two-stage robust optimisation approach and find solutions that minimise the worst-case project makespan, whilst assuming that activity durations lie in a budgeted uncertainty set. Computational experiments show that this easy-to-implement formulation is many times faster than the current state-of-the-art solution approach for this problem, whilst solving over 40% more instances to optimality over the same benchmarking set. {\textcopyright} 2022 The Author(s)",
keywords = "Budgeted uncertainty, Optimisation under uncertainty, Project scheduling, Robust optimisation",
author = "M. Bold and M. Goerigk",
year = "2022",
month = sep,
day = "30",
doi = "10.1016/j.orl.2022.08.003",
language = "English",
volume = "50",
pages = "581--587",
journal = "Operations Research Letters",
issn = "0167-6377",
publisher = "Elsevier",
number = "5",

}

RIS

TY - JOUR

T1 - A faster exact method for solving the robust multi-mode resource-constrained project scheduling problem

AU - Bold, M.

AU - Goerigk, M.

PY - 2022/9/30

Y1 - 2022/9/30

N2 - This paper presents a mixed-integer linear programming formulation for the multi-mode resource-constrained project scheduling problem with uncertain activity durations. We consider a two-stage robust optimisation approach and find solutions that minimise the worst-case project makespan, whilst assuming that activity durations lie in a budgeted uncertainty set. Computational experiments show that this easy-to-implement formulation is many times faster than the current state-of-the-art solution approach for this problem, whilst solving over 40% more instances to optimality over the same benchmarking set. © 2022 The Author(s)

AB - This paper presents a mixed-integer linear programming formulation for the multi-mode resource-constrained project scheduling problem with uncertain activity durations. We consider a two-stage robust optimisation approach and find solutions that minimise the worst-case project makespan, whilst assuming that activity durations lie in a budgeted uncertainty set. Computational experiments show that this easy-to-implement formulation is many times faster than the current state-of-the-art solution approach for this problem, whilst solving over 40% more instances to optimality over the same benchmarking set. © 2022 The Author(s)

KW - Budgeted uncertainty

KW - Optimisation under uncertainty

KW - Project scheduling

KW - Robust optimisation

U2 - 10.1016/j.orl.2022.08.003

DO - 10.1016/j.orl.2022.08.003

M3 - Journal article

VL - 50

SP - 581

EP - 587

JO - Operations Research Letters

JF - Operations Research Letters

SN - 0167-6377

IS - 5

ER -