Abstract
Inspired by the transmission of beans in nature, a novel swarm intelligence algorithm-Bean Optimization Algorithm (BOA) is proposed. In the area of continuous optimization problems solving, BOA has shown a good performance. In this paper, an improved BOA is presented for solving TSP, a typical discrete optimization problem. Two novel evolution mechanisms named population migration and priori information cross-sharing are proposed to improve the performance of BOA. The improved BOA algorithm maintains the basic idea of BOA and overcomes the shortcoming that BOA with continuous distribution function can not be applied to solve the discrete optimization problems. The experimental results of TSP show that the improved BOA algorithm is suit for solving discrete optimization problems with high efficiency.
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References
Dorigo, M., Birattari, M., Stützle, T.: Ant Colony Optimization– Artificial Ants as a Computational Intelligence Technique. IEEE Computational Intelligence Magazine 11(4), 28–39 (2006)
Kennedy, J.: The Particle Swarm: Social Adaptation of Knowledge. In: 1997 IEEE International Conference on Evolutionary Computation, pp. 303–308. IEEE Press, New York (1997)
Zhang, X., Wang, R., Song, L.: A Novel Evolutionary Algorithm—Seed Optimization Algorithm. Pattern Recognition and Artificial Intelligence 21(5), 677–681 (2008)
Wang, P., Cheng, Y.: Relief Supplies Scheduling Based on Bean Optimization Algorithm. Economic Research Guide (8), 252–253 (2010)
Zhang, X., Sun, B., Mei, T., Wang, R.: Post-disaster Restoration Based on Fuzzy Preference Relation and Bean Optimization Algorithm. In: 2010 IEEE Youth Conference on Information, Computing and Telecommunications, pp. 253–256. IEEE Press, New York (2010)
Li, Y.: Solving TSP by an ACO-and-BOA-based Hybrid Algorithm. In: 2010 International Conference on Computer Application and System Modeling, pp. 189–192. IEEE Press, New York (2010)
Mona Lisa TSP Challenge, http://www.tsp.gatech.edu/data/ml/mona-lisa100K.tsp
Stützle, T., Hoos, H.: MAX-MIN Ant System. Future Generation Computer Systems 16(8), 889–891 (2000)
Optimization Algorithm Toolkit, http://optalgtoolkit.sourceforge.net
Su, J., Wang, J.: Improved Particle Swarm Optimization for Traveling Salesman Problem. Computer Engineering and Applications 46(4), 52–75 (2010)
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© 2012 Springer-Verlag Berlin Heidelberg
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Zhang, X., Jiang, K., Wang, H., Li, W., Sun, B. (2012). An Improved Bean Optimization Algorithm for Solving TSP. In: Tan, Y., Shi, Y., Ji, Z. (eds) Advances in Swarm Intelligence. ICSI 2012. Lecture Notes in Computer Science, vol 7331. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30976-2_31
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DOI: https://doi.org/10.1007/978-3-642-30976-2_31
Publisher Name: Springer, Berlin, Heidelberg
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