Optimization of Supply Chain Network using Genetic Algorithms based on Bill of materials

Dennis Kallina and Patrick Siegfried

MPRA Paper from University Library of Munich, Germany

Abstract: 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.

Keywords: Supply Chain Network; Genetic Algorithm; Supply Chain Network Optimization (search for similar items in EconPapers)
JEL-codes: F63 L14 R41 (search for similar items in EconPapers)
Date: 2021-07-05
New Economics Papers: this item is included in nep-cmp and nep-ore
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Citations: View citations in EconPapers (1)

Published in International Journal of Engineering and Science (IJES) 7.10(2021): pp. 37-47

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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:111397

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