Abstract
Harmony search is a new heuristic optimization algorithm. Comparing with other algorithms, this algorithm has very strong robustness and can be easily operated. Combining with the features of harmony search, an improved simulated annealing algorithm is proposed in this paper. It can improve the speed of annealing. The initial state of simulated annealing and new solutions are generated by harmony search. So it has the advantage of high quality and efficiency. The simulation results show that this new algorithm has faster convergence speed and better optimization quality than the traditional simulated annealing algorithm and other algorithms.
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
Preview
Unable to display preview. Download preview PDF.
References
Geem, Z., Kim, J., Loganathan, G.: A New Heuristic Optimization Algorithm: Harmony Search. J. Simulation 76(2), 60–68 (2001)
Omran, M.G.H., Mahdavi, M.: Global-best Harmony Search. J. Applied Mathematics and Computation 198, 643–656 (2008)
Ling, W.: Intelligent Optimization Algorithm and its Application. Tsinghua University Press, Beijing (2001)
Jian, F., Qi, Y.: Solving TSP problem by Using Simulated Annealing Algorithm. J. Forest Engineering 24(1), 94–96 (2008)
Guohua, S., Yujin, C.: Improved Simulated Annealing Algorithm for Solving TSP problem. J. The Computer Knowledge and Technology 2(15), 1103–1105 (2008)
Jiangang, J., Juqun, L.: An Improved Simulated Annealing Algorithm to Solve Objective Optimization. J. Science and Technology Consulting Review 28, 148 (2007)
Pin, L., Jinfang, Z., Guan-bo, B., Lin, Y.: Research on Observer Sitting Problem Based on Improved Simulated Annealing Algorithm. J. Journal of System Simulation 21(14), 4328–4330 (2009)
Zhiyi, Q., Xuefei, W., Zhiming, F., Zhenming, S.: An Optimization Algorithm for Multiple Constrained QoS Multicast Routing based on Genetic and Simulated Annealing Algorithm. J. Computer Applications and Software 24(12), 182–184 (2007)
Shilian, Z., Zhijin, Z., Junna, S., Xiaoniu, Y.: Cognitive Radio Decision of Simulated Annealing based on Genetic algorithm. J. Computer Simulation 25(1), 192–196 (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Jiang, H., Liu, Y., Zheng, L. (2010). Design and Simulation of Simulated Annealing Algorithm with Harmony Search. In: Tan, Y., Shi, Y., Tan, K.C. (eds) Advances in Swarm Intelligence. ICSI 2010. Lecture Notes in Computer Science, vol 6146. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13498-2_59
Download citation
DOI: https://doi.org/10.1007/978-3-642-13498-2_59
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13497-5
Online ISBN: 978-3-642-13498-2
eBook Packages: Computer ScienceComputer Science (R0)