Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 51-56 |
| Seitenumfang | 6 |
| Fachzeitschrift | Procedia CIRP |
| Jahrgang | 96 |
| Frühes Online-Datum | 10 Feb. 2021 |
| Publikationsstatus | Veröffentlicht - 2021 |
| Veranstaltung | 8th CIRP Global Web Conference on Flexible Mass Customisation - Leuven, Belgien Dauer: 14 Okt. 2020 → 16 Okt. 2020 Konferenznummer: 8 |
Abstract
Higher customer requirements and increasing competitive pressure lead to a growing number of variants and smaller batch sizes in manufacturing. As a result, companies have to deal with challenges of small series manufacturing. A unidimensional set-up optimization cannot provide a satisfying solution. At the same time, production system-specific control algorithms are usually complex and require constant adaptation as customer requirements change continuously. To address these issues, this paper presents a hybrid genetic algorithm which allows modular sequence optimization in production scheduling. Hybrid elements are used to reach a high solution quality within a short runtime.
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Steuerungs- und Systemtechnik
- Ingenieurwesen (insg.)
- Wirtschaftsingenieurwesen und Fertigungstechnik
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in: Procedia CIRP, Jahrgang 96, 2021, S. 51-56.
Publikation: Beitrag in Fachzeitschrift › Konferenzaufsatz in Fachzeitschrift › Forschung › Peer-Review
}
TY - JOUR
T1 - Modular sequence optimization with hybrid genetic algorithm
AU - Denkena, B.
AU - Dittrich, M. A.
AU - Wilmsmeier, S.
AU - Settnik, S. J.
N1 - Conference code: 8
PY - 2021
Y1 - 2021
N2 - Higher customer requirements and increasing competitive pressure lead to a growing number of variants and smaller batch sizes in manufacturing. As a result, companies have to deal with challenges of small series manufacturing. A unidimensional set-up optimization cannot provide a satisfying solution. At the same time, production system-specific control algorithms are usually complex and require constant adaptation as customer requirements change continuously. To address these issues, this paper presents a hybrid genetic algorithm which allows modular sequence optimization in production scheduling. Hybrid elements are used to reach a high solution quality within a short runtime.
AB - Higher customer requirements and increasing competitive pressure lead to a growing number of variants and smaller batch sizes in manufacturing. As a result, companies have to deal with challenges of small series manufacturing. A unidimensional set-up optimization cannot provide a satisfying solution. At the same time, production system-specific control algorithms are usually complex and require constant adaptation as customer requirements change continuously. To address these issues, this paper presents a hybrid genetic algorithm which allows modular sequence optimization in production scheduling. Hybrid elements are used to reach a high solution quality within a short runtime.
KW - adaptivity
KW - Flowshop
KW - hybrid genetic algorithm
KW - modular design
KW - scheduling
KW - Sequencing
UR - http://www.scopus.com/inward/record.url?scp=85101174007&partnerID=8YFLogxK
U2 - 10.1016/j.procir.2021.01.052
DO - 10.1016/j.procir.2021.01.052
M3 - Conference article
AN - SCOPUS:85101174007
VL - 96
SP - 51
EP - 56
JO - Procedia CIRP
JF - Procedia CIRP
SN - 2212-8271
T2 - 8th CIRP Global Web Conference on Flexible Mass Customisation, CIRPe 2020
Y2 - 14 October 2020 through 16 October 2020
ER -