Scheduling in production, supply chain and Industry 4.0 systems by optimal control: fundamentals, state-of-the-art and applications. / Dolgui, Alexandre; Ivanov, Dmitry; Sethi, Suresh ; Sokolov, Boris .
In: International Journal of Production Research, Vol. 57, No. 2, 2019, p. 411-432.Research output: Contribution to journal › Article › peer-review
}
TY - JOUR
T1 - Scheduling in production, supply chain and Industry 4.0 systems by optimal control: fundamentals, state-of-the-art and applications
AU - Dolgui, Alexandre
AU - Ivanov, Dmitry
AU - Sethi, Suresh
AU - Sokolov, Boris
N1 - Alexandre Dolgui, Dmitry Ivanov, Suresh P. Sethi & Boris Sokolov. Scheduling in production, supply chain and Industry 4.0 systems by optimal control: fundamentals, state-of-the-art and applications // International Journal of Production Research. 2019. Vol. 57. Issue 2. P.411-432. ISSN: 0020-7543 (Print) 1366-588X (Online) Journal homepage: http://www.tandfonline.com/loi/tprs20. https://doi.org/10.1080/00207543.2018.1442948
PY - 2019
Y1 - 2019
N2 - This paper presents a survey on the applications of optimal control to scheduling in production, supply chain and Industry 4.0 systems with a focus on the deterministic maximum principle. The first objective is to derive major contributions, application areas, limitations, as well as research and application recommendations for the future research. The second objective is to explain control engineering models in terms of industrial engineering and production management. To achieve these objectives, optimal control models, qualitative methods of performance analysis and computational methods for optimal control are considered. We provide a brief historic overview and clarify major mathematical fundamentals whereby the control engineering terms are brought into correspondence with industrial engineering and management. The survey allows the grouping of models with only terminal constraints with application to master production scheduling, models with hybrid terminal–logical constraints with applications to short term job and flow shop scheduling, and hybrid structural–terminal–logical constraints with applications to customised assembly systems such as Industry 4.0. Computational algorithms in state, control and adjoint variable spaces are discussed.
AB - This paper presents a survey on the applications of optimal control to scheduling in production, supply chain and Industry 4.0 systems with a focus on the deterministic maximum principle. The first objective is to derive major contributions, application areas, limitations, as well as research and application recommendations for the future research. The second objective is to explain control engineering models in terms of industrial engineering and production management. To achieve these objectives, optimal control models, qualitative methods of performance analysis and computational methods for optimal control are considered. We provide a brief historic overview and clarify major mathematical fundamentals whereby the control engineering terms are brought into correspondence with industrial engineering and management. The survey allows the grouping of models with only terminal constraints with application to master production scheduling, models with hybrid terminal–logical constraints with applications to short term job and flow shop scheduling, and hybrid structural–terminal–logical constraints with applications to customised assembly systems such as Industry 4.0. Computational algorithms in state, control and adjoint variable spaces are discussed.
UR - https://www.tandfonline.com/doi/full/10.1080/00207543.2018.1442948
M3 - Article
VL - 57
SP - 411
EP - 432
JO - International Journal of Production Research
JF - International Journal of Production Research
SN - 0020-7543
IS - 2
ER -
ID: 62144492