Abstract
The automotive industry is constantly facing the challenge of optimizing their suppliers to meet customer demands while keeping costs low. Knowledge graphs have proven to be effective tools for modeling complex supply chains, but their use for optimization is limited. In this paper, we report on our experience at Bosch to use Answer Set Programming (ASP) to optimize component suppliers in the automotive industry based on knowledge graphs. Evaluation on industrial products shows both efficiency and effectiveness of our modeling framework in generating optimal solutions for supply chain management problems.
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CITATION STYLE
Chu, C. X., Gad-Elrab, M. H., Tran, T. K., Schiller, M., Kharlamov, E., & Stepanova, D. (2023). Supplier Optimization at Bosch with Knowledge Graphs and Answer Set Programming. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13998 LNCS, pp. 200–204). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-43458-7_38
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