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Robust balancing of transfer lines with blocks of uncertain parallel tasks under fixed cycle time and space restrictions

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

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Robust balancing of transfer lines with blocks of uncertain parallel tasks under fixed cycle time and space restrictions. / Pirogov, Aleksandr; Gurevsky, Evgeny; Rossi, Andre et al.
In: European Journal of Operational Research, Vol. 290, No. 3, 01.05.2021, p. 946-955.

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

Harvard

Pirogov, A, Gurevsky, E, Rossi, A & Dolgui, A 2021, 'Robust balancing of transfer lines with blocks of uncertain parallel tasks under fixed cycle time and space restrictions', European Journal of Operational Research, vol. 290, no. 3, pp. 946-955. https://doi.org/10.1016/j.ejor.2020.08.038

APA

Pirogov, A., Gurevsky, E., Rossi, A., & Dolgui, A. (2021). Robust balancing of transfer lines with blocks of uncertain parallel tasks under fixed cycle time and space restrictions. European Journal of Operational Research, 290(3), 946-955. https://doi.org/10.1016/j.ejor.2020.08.038

Vancouver

Pirogov A, Gurevsky E, Rossi A, Dolgui A. Robust balancing of transfer lines with blocks of uncertain parallel tasks under fixed cycle time and space restrictions. European Journal of Operational Research. 2021 May 1;290(3):946-955. Epub 2021 Jan 4. doi: 10.1016/j.ejor.2020.08.038

Author

Pirogov, Aleksandr ; Gurevsky, Evgeny ; Rossi, Andre et al. / Robust balancing of transfer lines with blocks of uncertain parallel tasks under fixed cycle time and space restrictions. In: European Journal of Operational Research. 2021 ; Vol. 290, No. 3. pp. 946-955.

Bibtex

@article{32dd62010ae646bf8592015d194011c4,
title = "Robust balancing of transfer lines with blocks of uncertain parallel tasks under fixed cycle time and space restrictions",
abstract = "This paper deals with an optimization problem, which arises when a new transfer line has to be designed subject to a limited number of available machines, cycle time constraint, and precedence relations between necessary production tasks. The studied problem consists in assigning a given set of tasks to blocks and then blocks to machines so as to find the most robust line configuration under task processing time uncertainty. The robustness of a given line configuration is measured via its stability radius, i.e., as the maximal amplitude of deviations from the nominal value of the processing time of uncertain tasks that do not violate the solution admissibility. In this work, for considering different hypotheses on uncertainty, the stability radius is based upon the Manhattan and Chebyshev norms. For each norm, the problem is proven to be strongly NP-hard and a mixed-integer linear program (MILP) is proposed for addressing it. To accelerate the seeking of optimal solutions, two variants of a heuristic method as well as several reduction rules are devised for the corresponding MILP. Computational results are reported on a collection of instances derived from classic benchmark data used in the literature for the Transfer Line Balancing Problem.",
keywords = "Manufacturing, Transfer line, Balancing, Stability radius, Robustness, Uncertainty, Robust optimization, MILP, Heuristics, Pre-processing",
author = "Aleksandr Pirogov and Evgeny Gurevsky and Andre Rossi and Alexandre Dolgui",
year = "2021",
month = may,
day = "1",
doi = "10.1016/j.ejor.2020.08.038",
language = "English",
volume = "290",
pages = "946--955",
journal = "European Journal of Operational Research",
issn = "0377-2217",
publisher = "Elsevier Science B.V.",
number = "3",

}

RIS

TY - JOUR

T1 - Robust balancing of transfer lines with blocks of uncertain parallel tasks under fixed cycle time and space restrictions

AU - Pirogov, Aleksandr

AU - Gurevsky, Evgeny

AU - Rossi, Andre

AU - Dolgui, Alexandre

PY - 2021/5/1

Y1 - 2021/5/1

N2 - This paper deals with an optimization problem, which arises when a new transfer line has to be designed subject to a limited number of available machines, cycle time constraint, and precedence relations between necessary production tasks. The studied problem consists in assigning a given set of tasks to blocks and then blocks to machines so as to find the most robust line configuration under task processing time uncertainty. The robustness of a given line configuration is measured via its stability radius, i.e., as the maximal amplitude of deviations from the nominal value of the processing time of uncertain tasks that do not violate the solution admissibility. In this work, for considering different hypotheses on uncertainty, the stability radius is based upon the Manhattan and Chebyshev norms. For each norm, the problem is proven to be strongly NP-hard and a mixed-integer linear program (MILP) is proposed for addressing it. To accelerate the seeking of optimal solutions, two variants of a heuristic method as well as several reduction rules are devised for the corresponding MILP. Computational results are reported on a collection of instances derived from classic benchmark data used in the literature for the Transfer Line Balancing Problem.

AB - This paper deals with an optimization problem, which arises when a new transfer line has to be designed subject to a limited number of available machines, cycle time constraint, and precedence relations between necessary production tasks. The studied problem consists in assigning a given set of tasks to blocks and then blocks to machines so as to find the most robust line configuration under task processing time uncertainty. The robustness of a given line configuration is measured via its stability radius, i.e., as the maximal amplitude of deviations from the nominal value of the processing time of uncertain tasks that do not violate the solution admissibility. In this work, for considering different hypotheses on uncertainty, the stability radius is based upon the Manhattan and Chebyshev norms. For each norm, the problem is proven to be strongly NP-hard and a mixed-integer linear program (MILP) is proposed for addressing it. To accelerate the seeking of optimal solutions, two variants of a heuristic method as well as several reduction rules are devised for the corresponding MILP. Computational results are reported on a collection of instances derived from classic benchmark data used in the literature for the Transfer Line Balancing Problem.

KW - Manufacturing

KW - Transfer line

KW - Balancing

KW - Stability radius

KW - Robustness

KW - Uncertainty

KW - Robust optimization

KW - MILP

KW - Heuristics

KW - Pre-processing

U2 - 10.1016/j.ejor.2020.08.038

DO - 10.1016/j.ejor.2020.08.038

M3 - Journal article

VL - 290

SP - 946

EP - 955

JO - European Journal of Operational Research

JF - European Journal of Operational Research

SN - 0377-2217

IS - 3

ER -