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

Dmitry Ivanov, Alexandre Dolgui, Boris Sokolov, Frank Werner, Marina Ivanova

Результат исследований: Научные публикации в периодических изданияхстатьярецензирование

276 Цитирования (Scopus)

Аннотация

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.

Язык оригиналаанглийский
Страницы (с-по)386-402
Число страниц17
ЖурналInternational Journal of Production Research
Том54
Номер выпуска2
DOI
СостояниеОпубликовано - 17 янв 2016

Предметные области Scopus

  • Стратегия и управление
  • Теория управления и исследование операций
  • Промышленная технология и станкостроение

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