Exploiting landscape features for fitness prediction in university timetabling

Author:

Feutrier Thomas1,Veerapen Nadarajen1,Kessaci Marie-Éléonore1

Affiliation:

1. Univ. Lille, Lille, France

Publisher

ACM

Reference15 articles.

1. Daolio , F. , Liefooghe , A. , Verel , S. , Aguirre , H. , Tanaka , K. : Problem Features vs. Algorithm Performance on Rugged Multiobjective Combinatorial Fitness Landscapes. Evolutionary Computation 25 ( 4 ), 555 -- 585 ( 2017 ) Daolio, F., Liefooghe, A., Verel, S., Aguirre, H., Tanaka, K.: Problem Features vs. Algorithm Performance on Rugged Multiobjective Combinatorial Fitness Landscapes. Evolutionary Computation 25(4), 555--585 (2017)

2. Investigating the landscape of a hybrid local search approach for a timetabling problem

3. PageRank centrality for performance prediction: the impact of the local optima network model

4. Kohavi , R. : A study of cross-validation and bootstrap for accuracy estimation and model selection . In: Proceedings of the 14th International Joint Conference on Artificial Intelligence - Volume 2 . p. 1137 -- 1143 . IJCAI'95, Morgan Kaufmann Publishers Inc., San Francisco, CA, USA ( 1995 ) Kohavi, R.: A study of cross-validation and bootstrap for accuracy estimation and model selection. In: Proceedings of the 14th International Joint Conference on Artificial Intelligence - Volume 2. p. 1137--1143. IJCAI'95, Morgan Kaufmann Publishers Inc., San Francisco, CA, USA (1995)

5. Landscape-Aware Performance Prediction for Evolutionary Multiobjective Optimization

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