Abstract
In this paper, we describe a modified fireworks algorithm (MFWA) for the multi-resource range scheduling problem which is a highly constrained combinatorial optimization problem. Fireworks algorithm (FWA) is a meta-heuristic method inspired by fireworks explosion at night. The basic components of FWA consist of a local search phase and a selection phase. In the local search phase, explosion sparks are generated with genetic strategy, and Gaussian sparks are produced through interchange operator. In the selection phase, a disparity metric is introduced so as to select representative solutions for the next generation. The experimental results demonstrate this MFWA is more competitive than the original FWA as well as the other two commonly used methods.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
References
Zweben, M., Davis, E., Daun, B., Deale, M.J.: Scheduling and rescheduling with iterative repair. IEEE Trans. Syst. Man Cybern. 23(6), 1588–1596 (1993)
Barbulescu, L., Howe, A.E., Watson, J.-P., Whitley, L.D.: Satellite range scheduling: a comparison of genetic, heuristic and local search. In: Guervós, J.J.M., Adamidis, P.A., Beyer, H.-G., Fernández-Villacañas, J.-L., Schwefel, H.-P. (eds.) PPSN 2002. LNCS, vol. 2439, p. 611. Springer, Heidelberg (2002)
Barbulescu, L., Watson, J.P., Whitley, L.D., Howe, A.E.: Scheduling spaceCground communications for the air force satellite control network. J. Sched. 7(1), 7–34 (2004)
Zhang, N., Feng, Z.R., Ke, L.J.: Guidance-solution based ant colony optimization for satellite control resource scheduling problem. Appl. Intell. 35(3), 436–444 (2011)
Zhang, Z., Zhang, N., Feng, Z.: Multi-satellite control resource scheduling based on ant colony optimization. Expert Syst. Appl. 41(6), 2816–2823 (2014)
Liu, Z., Feng, Z., Ke, L.: Fireworks algorithm for the multi-satellite control resource scheduling problem. In: 2015 IEEE Congress on Evolutionary Computation (CEC), pp. 1280–1286. IEEE, May 2015
Tan, Y., Zhu, Y.: Fireworks algorithm for optimization. In: Tan, Y., Shi, Y., Tan, K.C. (eds.) ICSI 2010, Part I. LNCS, vol. 6145, pp. 355–364. Springer, Heidelberg (2010)
Janecek, A., Tan, Y.: Swarm intelligence for non-negative matrix factorization. Recent Algorithms and Applications in Swarm Intelligence Research, 168 (2012)
Zheng, S., Tan, Y.: A unified distance measure scheme for orientation coding in identification. In: 2013 International Conference on Information Science and Technology (ICIST), pp. 979–985. IEEE, March 2013
Jones, T., Forrest, S.: Fitness distance correlation as a measure of problem difficulty for genetic algorithms. In: ICGA, vol. 95, pp. 184–192, July 1995
Acknowledgments
This work was supported by the Fundamental Research Funds for the Central Universities, the Open Research Fund of the State Key Laboratory of Astronautic Dynamics under Grant 2014ADL-DW402, the Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry, and State Key Laboratory of Intelligent Control and Decision of Complex Systems. We are also thankful to the anonymous referees.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Liu, Z., Feng, Z., Ke, L. (2016). A Modified Fireworks Algorithm for the Multi-resource Range Scheduling Problem. In: Tan, Y., Shi, Y., Niu, B. (eds) Advances in Swarm Intelligence. ICSI 2016. Lecture Notes in Computer Science(), vol 9712. Springer, Cham. https://doi.org/10.1007/978-3-319-41000-5_53
Download citation
DOI: https://doi.org/10.1007/978-3-319-41000-5_53
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-40999-3
Online ISBN: 978-3-319-41000-5
eBook Packages: Computer ScienceComputer Science (R0)