Dynamic online optimization in the context of smart manufacturing: An overview

Viktoria A. Hauder, Andreas Beham, Stefan Wagner, Karl F. Doerner, Michael Affenzeller

Research output: Contribution to journalConference articlepeer-review

5 Citations (Scopus)


Solving manufacturing optimization problems in the context of intelligent production involves the consideration of continuously changing events of the respective enterprise environment in real time. Smart solution methods are needed which are able to cope with such necessary reactions to uncertainty and dynamics. In general, this field of research belongs to the topic of dynamic optimization. However, investigating the relevant literature reveals the broad range of this research area. In addition to real time, i.e. online optimization it contains a large number of other (dynamic) sectors. After differentiating dynamic online optimization from other research domains of dynamic optimization, the aim of this work is (1) to show in which streams and problem fields it has already been investigated, and (2) which different approaches to categorize online optimization problems are known so far. As a result, an overview of the state of the art concerning the occurence and existing categorizations of online optimization problems in the context of smart manufacturing is given, demonstrating ambiguities in the language used and in the categorization efforts for this optimization problem and therefore motivating further research efforts on a comprehensive integration of the findings of different streams in this area.

Original languageEnglish
Pages (from-to)988-995
Number of pages8
JournalProcedia Computer Science
Publication statusPublished - 2021
Event2nd International Conference on Industry 4.0 and Smart Manufacturing, ISM 2020 - Virtual, Online, Austria
Duration: 23 Nov 202025 Nov 2020


  • categorization
  • Dynamic online optimization
  • real time
  • smart manufacturing
  • uncertainty


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