A dynamic model and an algorithm for short-term supply chain scheduling in the smart factory industry 4.0

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A dynamic model and an algorithm for short-term supply chain scheduling in the smart factory industry 4.0. / Ivanov, Dmitry; Dolgui, Alexandre; Sokolov, Boris; Werner, Frank; Ivanova, Marina.

в: International Journal of Production Research, Том 54, № 2, 17.01.2016, стр. 386-402.

Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование

Author

Ivanov, Dmitry ; Dolgui, Alexandre ; Sokolov, Boris ; Werner, Frank ; Ivanova, Marina. / A dynamic model and an algorithm for short-term supply chain scheduling in the smart factory industry 4.0. в: International Journal of Production Research. 2016 ; Том 54, № 2. стр. 386-402.

BibTeX

@article{fc1fcbd328374d5caaeebedcf55ea017,

title = "A dynamic model and an algorithm for short-term supply chain scheduling in the smart factory industry 4.0",

abstract = "Smart factories Industry 4.0 on the basis of collaborative cyber-physical systems represents a future form of industrial networks. Supply chains in such networks have dynamic structures which evolve over time. In these settings, short-term supply chain scheduling in smart factories Industry 4.0 is challenged by temporal machine structures, different processing speed at parallel machines and dynamic job arrivals. In this study, for the first time, a dynamic model and algorithm for short-term supply chain scheduling in smart factories Industry 4.0 is presented. The peculiarity of the considered problem is the simultaneous consideration of both machine structure selection and job assignments. The scheduling approach is based on a dynamic non-stationary interpretation of the execution of the jobs and a temporal decomposition of the scheduling problem. The algorithmic realisation is based on a modified form of the continuous maximum principle blended with mathematical optimisation. A detailed theoretical analysis of the temporal decomposition and computational complexity is performed. The optimality conditions as well as the structural properties of the model and the algorithm are investigated. Advantages and limitations of the proposed approach are discussed.",

keywords = "Alternative machines, Flexible flow shop, Optimal programme control, Smart factory, Structure dynamics, Supply chain scheduling",

author = "Dmitry Ivanov and Alexandre Dolgui and Boris Sokolov and Frank Werner and Marina Ivanova",

year = "2016",

month = jan,

day = "17",

doi = "10.1080/00207543.2014.999958",

language = "English",

volume = "54",

pages = "386--402",

journal = "International Journal of Production Research",

issn = "0020-7543",

publisher = "Taylor & Francis",

number = "2",

}

RIS

TY - JOUR

T1 - A dynamic model and an algorithm for short-term supply chain scheduling in the smart factory industry 4.0

AU - Ivanov, Dmitry

AU - Dolgui, Alexandre

AU - Sokolov, Boris

AU - Werner, Frank

AU - Ivanova, Marina

PY - 2016/1/17

Y1 - 2016/1/17

N2 - Smart factories Industry 4.0 on the basis of collaborative cyber-physical systems represents a future form of industrial networks. Supply chains in such networks have dynamic structures which evolve over time. In these settings, short-term supply chain scheduling in smart factories Industry 4.0 is challenged by temporal machine structures, different processing speed at parallel machines and dynamic job arrivals. In this study, for the first time, a dynamic model and algorithm for short-term supply chain scheduling in smart factories Industry 4.0 is presented. The peculiarity of the considered problem is the simultaneous consideration of both machine structure selection and job assignments. The scheduling approach is based on a dynamic non-stationary interpretation of the execution of the jobs and a temporal decomposition of the scheduling problem. The algorithmic realisation is based on a modified form of the continuous maximum principle blended with mathematical optimisation. A detailed theoretical analysis of the temporal decomposition and computational complexity is performed. The optimality conditions as well as the structural properties of the model and the algorithm are investigated. Advantages and limitations of the proposed approach are discussed.

AB - Smart factories Industry 4.0 on the basis of collaborative cyber-physical systems represents a future form of industrial networks. Supply chains in such networks have dynamic structures which evolve over time. In these settings, short-term supply chain scheduling in smart factories Industry 4.0 is challenged by temporal machine structures, different processing speed at parallel machines and dynamic job arrivals. In this study, for the first time, a dynamic model and algorithm for short-term supply chain scheduling in smart factories Industry 4.0 is presented. The peculiarity of the considered problem is the simultaneous consideration of both machine structure selection and job assignments. The scheduling approach is based on a dynamic non-stationary interpretation of the execution of the jobs and a temporal decomposition of the scheduling problem. The algorithmic realisation is based on a modified form of the continuous maximum principle blended with mathematical optimisation. A detailed theoretical analysis of the temporal decomposition and computational complexity is performed. The optimality conditions as well as the structural properties of the model and the algorithm are investigated. Advantages and limitations of the proposed approach are discussed.

KW - Alternative machines

KW - Flexible flow shop

KW - Optimal programme control

KW - Smart factory

KW - Structure dynamics

KW - Supply chain scheduling

UR - http://www.scopus.com/inward/record.url?scp=84955677643&partnerID=8YFLogxK

U2 - 10.1080/00207543.2014.999958

DO - 10.1080/00207543.2014.999958

M3 - Article

AN - SCOPUS:84955677643

VL - 54

SP - 386

EP - 402

JO - International Journal of Production Research

JF - International Journal of Production Research

SN - 0020-7543

IS - 2

ER -

ID: 62143446