Learning
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-31785-9_6
Reference10 articles.
1. Guo, W., Vanhoucke, M., & Coelho, J. (2023a). Detecting the best performing branch-and-bound procedures for the resource-constrained project scheduling problem via machine learning. Working Paper (under submission).
2. Guo, W., Vanhoucke, M., & Coelho, J. (2023b). A prediction model for ranking branch-and-bound procedures for the resource-constrained project scheduling problem. European Journal of Operational Research, 306, 579–595.
3. Guo, W., Vanhoucke, M., Coelho, J., & Luo, J. (2021). Automatic detection of the best performing priority rule for the resource-constrained project scheduling problem. Expert Systems with Applications, 167, 114116.
4. Luo, J., Vanhoucke, M., & Coelho, J. (2023). Automated design of priority rules for resource-constrained project scheduling problem using surrogate-assisted genetic programming. Swarm and Evolutionary Computation, forthcoming (doi: https://10.1016/j.swevo.2023.101339)
5. Luo, J., Vanhoucke, M., Coelho, J., & Guo, W. (2022). An efficient genetic programming approach to design priority rules for resource-constrained project scheduling problem. Expert Systems with Applications, 198, 116753.
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