Lazy Conflict Detection with Genetic Algorithms

Christoph Uran; Alexander Felfernig

doi:10.1007/978-3-319-92058-017

Lazy Conflict Detection with Genetic Algorithms

Christoph Uran
, Alexander Felfernig

Institute of Software Engineering and Artificial Intelligence (7160)

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

Original language	English
Title of host publication	Recent Trends and Future Technology in Applied Intelligence - 31st International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2018, Montreal, QC, Canada, June 25-28, 2018, Proceedings
Pages	175-186
Number of pages	12
DOIs	https://doi.org/10.1007/978-3-319-92058-017
Publication status	Published - 2018

Access to Document

10.1007/978-3-319-92058-017

https://doi.org/10.1007/978-3-319-92058-017

Cite this

Uran, C., & Felfernig, A. (2018). Lazy Conflict Detection with Genetic Algorithms. In Recent Trends and Future Technology in Applied Intelligence - 31st International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2018, Montreal, QC, Canada, June 25-28, 2018, Proceedings (pp. 175-186) https://doi.org/10.1007/978-3-319-92058-017

Lazy Conflict Detection with Genetic Algorithms. / Uran, Christoph; Felfernig, Alexander.
Recent Trends and Future Technology in Applied Intelligence - 31st International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2018, Montreal, QC, Canada, June 25-28, 2018, Proceedings. 2018. p. 175-186.

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

Uran, C & Felfernig, A 2018, Lazy Conflict Detection with Genetic Algorithms. in Recent Trends and Future Technology in Applied Intelligence - 31st International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2018, Montreal, QC, Canada, June 25-28, 2018, Proceedings. pp. 175-186. https://doi.org/10.1007/978-3-319-92058-017

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