Integrating the multi-objective particle swarm optimization-based time–cost trade-off model with earned value management
Author:
Publisher
Springer Science and Business Media LLC
Subject
Civil and Structural Engineering
Link
https://link.springer.com/content/pdf/10.1007/s42107-023-00710-5.pdf
Reference34 articles.
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2. Aminbakhsh, S., & Sonmez, R. (2016). Discrete particle swarm optimization method for the large-scale discrete time-cost trade-off problem. Expert Systems with Applications, 51(2016), 177–185. https://doi.org/10.1016/j.eswa.2015.12.041
3. Anagnostopoulos, K. P., & Kotsikas, L. (2010). Experimental evaluation of simulated annealing algorithms for the time-cost trade-off problem. Applied Mathematics and Computation. https://doi.org/10.1016/j.amc.2010.05.056
4. Di, C., Sun, F. Q., Liu, S. X., & Wang, Y. F. (2013). Priority rule based heuristics for project scheduling problems with multi-skilled workforce constraints. 2013 25th Chinese Control and Decision Conference, CCDC 2013. https://doi.org/10.1109/CCDC.2013.6561233
5. Elmaghraby, S. E. (1977). Activity networks: project planning and control by network models. New York: Wiley.
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1. Improving the effectiveness of project scheduling by using Earned Value Management and Artificial Neural Network;Revista Ingeniería de Construcción;2024-08
2. Augmented Time–Cost Trade-Off Optimization Using Particle Swarm Optimization;Journal of Construction Engineering and Management;2024-05
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