Abstract
A Dynamic Clonal Selection Algorithm for the Resource-Constrained Project Scheduling Problem (RCPSP-DCSA) is proposed in this paper. Based on the mechanism of nature immune system and characteristic of project scheduling, the encoding of solution, some operators (including crossover, mutation, deriving and death) and the function of affinity are given. Through a thorough computational study for a standard set of project instances in PSPLIB, the impact of the parameters on the performance of algorithm are analyzed. Experimental results show RCPSP-DCSA has a good performance and it can reach near-optimal solutions in reasonable time.
Supported by the National Natural Science Foundation of China under Grant Nos. 60372045 and the National Grand Fundamental Research 973 Program of China under Grant No. 2001CB309403.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Kis, T.: A branch-and-cut algorithm for scheduling of projects with variable-intensity activities. Mathematical Programming 103, 515–539 (2005)
Thomas, P.R., Salhi, S.: A Tabu Search Approach for the Resource Constrained Project Scheduling Problem. Journal of Heuristics (4), 123–139 (2001)
Bautista, J., Pereira, J.: Ant colonies for the RCPSP Problem. In: Topics in Artificial Intelligence: 5th Catalonian Conference on AI, CCIA 2002, Castell’on, Spain, October 24-25, 2002, pp. 257–268 (2002)
Hindi, K.S., Yang, H., Fleszar, K.: An Evolutionary Algorithm for Resource-Constrained Project Scheduling. IEEE Transactions on Evolutionary Computation (6), 512–518 (2002)
Debels, D., Vanhoucke, M.: A Bi-population Based Genetic Algorithm for the Resource-Constrained Project Scheduling Problem. In: Computational Science and Its Applications-ICCSA 2005: International Conference. Proceedings, Part IV, Singapore, May 9-12, 2005, pp. 378–387 (2005)
Wang, H., Lin, D.: A Genetic Algorithm for Solving Resource-Constrained Project Scheduling Problem. In: Wang, L., Chen, K., S. Ong, Y. (eds.) ICNC 2005. LNCS, vol. 3610, pp. 185–193. Springer, Heidelberg (2005)
Valls, V., Ballestn, F.: A Population-Based Approach to the Resource- Constrained Project Scheduling Problem. Annals of Operations Research (131), 305–324 (2004)
Kolisch, R., Hartmann, S.: Experimental Investigation of Heuristics for Resource-Constrained Project Scheduling: An Update. European Journal of Operational Research (to appear, 2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Pan, X., Liu, F., Jiao, L. (2006). A Dynamic Clonal Selection Algorithm for Project Optimization Scheduling. In: Wang, TD., et al. Simulated Evolution and Learning. SEAL 2006. Lecture Notes in Computer Science, vol 4247. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11903697_103
Download citation
DOI: https://doi.org/10.1007/11903697_103
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-47331-2
Online ISBN: 978-3-540-47332-9
eBook Packages: Computer ScienceComputer Science (R0)