TY - JOUR
T1 - Dynamic online optimization in the context of smart manufacturing
T2 - 2nd International Conference on Industry 4.0 and Smart Manufacturing, ISM 2020
AU - Hauder, Viktoria A.
AU - Beham, Andreas
AU - Wagner, Stefan
AU - Doerner, Karl F.
AU - Affenzeller, Michael
N1 - Publisher Copyright:
© 2021 The Author(s).
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - categorization
KW - Dynamic online optimization
KW - real time
KW - smart manufacturing
KW - uncertainty
UR - https://www.scopus.com/pages/publications/85101780141
U2 - 10.1016/j.procs.2021.01.356
DO - 10.1016/j.procs.2021.01.356
M3 - Conference article
AN - SCOPUS:85101780141
VL - 180
SP - 988
EP - 995
JO - Procedia Computer Science
JF - Procedia Computer Science
Y2 - 23 November 2020 through 25 November 2020
ER -