Optimization of supply chain network using genetic algorithms based on bill of materials
- The integration of genetic algorithms to optimize the networks of value chains could enormously improve the performance of supply chains. For this reason, this paper describes in more detail the application of genetic algorithms in the value chains of the automotive industry. For this purpose, a theoretical model is built up to evaluate whether the application of the model can optimize the value chain. This option is described, analyzed and its restrictions are shown. Instead of looking at the entire network, individual finished goods and their bill of material are used as a basis for optimization, which greatly reduces the complexity of the original problem. The original complexity of the supply chain networks can thus be reduced and considered based on the bill of material.
Author: | Dennis Kallina, Patrick SiegfriedORCiD |
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URN: | urn:nbn:de:hbz:tr5-2324 |
Parent Title (English): | International Journal of Engineering & Science |
Publisher: | THE IJES |
Document Type: | Article (specialist journals) |
Language: | English |
Date of OPUS upload: | 2023/01/26 |
Year of first Publication: | 2021 |
Publishing University: | Hochschule Trier |
Release Date: | 2023/01/26 |
Tag: | genetic algorithm; supply chain network; supply chain network optimization |
GND Keyword: | Supply Chain Management; Wertschöpfungskette; Optimierung; Genetischer Algorithmus; Stückliste |
Volume: | 10 |
Issue: | 7 |
Page Number: | 11 |
First Page: | 37 |
Last Page: | 47 |
Note: | DOI-Angabe: 10.9790/1813-1007013747 zum Zeitpunkt des OPUS-Uploads inkorrekt oder noch nicht aktiviert |
Departments: | FB Bauen + Leben |
Dewey Decimal Classification: | 3 Sozialwissenschaften / 33 Wirtschaft |
Licence (German): | Creative Commons - CC BY-NC - Namensnennung - Nicht kommerziell 4.0 International |