An Experience Report on the Optimization of the Product Configuration System of Renault
From LRDE
- Authors
- Hao Xu, Souheib Baarir, Tewfik Ziadi, Siham EssodaiguiYves Bossu, Lom Messan Hillah
- Where
- 26th International Conference on Engineering of Complex Computer Systems
- Type
- proceedings"proceedings" is not in the list (article, incollection, inproceedings, misc, phdthesis, techreport) of allowed values for the "Publication type" property.
- Publisher
- IEEE
- Projects
- AA"AA" is not in the list (Vaucanson, Spot, URBI, Olena, APMC, Tiger, Climb, Speaker ID, Transformers, Bison, ...) of allowed values for the "Related project" property.
- Date
- 2023-04-03
Abstract
The problem of configuring a variability model is widespread in many different domains. A leading automobile manufacturer has developed its technology internally to model vehicle diversity. This technology relies on the approach known as knowledge compilation to explore the configurations space. However, the growing variability and complexity of the vehicles' range hardens the space representation problem and impacts performance requirements. This paper tackles these issues by exploiting symmetries that represent isomorphic parts in the configurations space. A new method describes how these symmetries are exploited and integrated. The extensive experiments we conducted on datasets from the automobile manufacturer show our approach's robustness and effectiveness: the achieved gain is a reduction of 52.13% in space representation and 49.81% in processing time on average
Bibtex (lrde.bib)
@Proceedings{ xu.23.iceccs, author = {Hao Xu and Souheib Baarir and Tewfik Ziadi and Siham Essodaigui, Yves Bossu and Lom Messan Hillah}, title = {An Experience Report on the Optimization of the Product Configuration System of Renault}, booktitle = {26th International Conference on Engineering of Complex Computer Systems}, publisher = {IEEE}, year = {2023}, month = jun, abstract = {The problem of configuring a variability model is widespread in many different domains. A leading automobile manufacturer has developed its technology internally to model vehicle diversity. This technology relies on the approach known as knowledge compilation to explore the configurations space. However, the growing variability and complexity of the vehicles' range hardens the space representation problem and impacts performance requirements. This paper tackles these issues by exploiting symmetries that represent isomorphic parts in the configurations space. A new method describes how these symmetries are exploited and integrated. The extensive experiments we conducted on datasets from the automobile manufacturer show our approach's robustness and effectiveness: the achieved gain is a reduction of 52.13\% in space representation and 49.81\% in processing time on average }, note = {To Appear} }