A data-driven meta-learning recommendation model for multi-mode resource constrained project scheduling problem

Author:

Chu Xianghua,Li Shuxiang,Gao Fei,Cui CanORCID,Pfeiffer Forest,Cui Jianshuang

Funder

National Natural Science Foundation of China

Natural Science Foundation of Guangdong Province

Publisher

Elsevier BV

Subject

Management Science and Operations Research,Modeling and Simulation,General Computer Science

Reference83 articles.

1. Generalizing from case studies: a case study;Aha,1992

2. Ahmeti, A., & Musliu, N. , 2021. Hybridizing constraint programming and meta-heuristics for multi-mode resource-constrained multiple projects scheduling problem. . In Proceedings of the 13th International Conference on the Practice and Theory of Automated Timetabling-PATAT (Vol. 1).

3. Combining Monte-Carlo and hyper-heuristic methods for the multi-mode resource-constrained multi-project scheduling problem;Asta;Information Sciences,2016

4. N. Bhatt, A.T., A. Ganatra, 2012. A survey & current research challenges in meta learning approaches based on dataset characteristics. International Journal of Soft Computing 2, 239-247. 10.1.1.683.8572.

5. Bishop, C.M., 2006. Pattern Recognition and Machine Learning. in: Information Science and Statistics, Springer-Verlag New York. https://link.springer.com/book/9780387310732.

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