教授
博士生导师
硕士生导师
主要任职：自动化学院讲座教授
性别：男
毕业院校：东北大学
学历：博士研究生毕业
学位：博士学位
所在单位：自动化学院
学科：计算机科学与技术 自动化
联系方式：电子邮件
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最后更新时间：..
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[21] H. Wang, S. Yang, W. H. Ip, and D. Wang. A particle swarm optimization based memetic algorithm for dynamic optimization problems. Natural Computing, 9(3): 703-725, September 2010. Springer (DOI: 10.1007/s11047-009-9176-2 and PDF File).
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[22] L. Liu, S. Yang, and D. Wang. Particle swarm optimization with composite particles in dynamic environments. IEEE Transactions on Systems, Man, and Cybernetics Part B: Cybernetics, 40(6): 1634-1648, December 2010. IEEE Press (DOI: 10.1109/TSMCB.2010.2043527 and PDF File).
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[23] S. Yang and S. N. Jat. Genetic algorithms with guided and local search strategies for university course timetabling. IEEE Transactions on Systems, Man, and Cybernetics Part C: Applications and Reviews, 41(1): 93-106, January 2011. IEEE Press (DOI: 10.1109/TSMCC.2010.2049200 and PDF File).
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[24] X. Peng, X. Gao, and S. Yang. Environment identification based memory scheme for estimation of distribution algorithms in dynamic environments. Soft Computing, 15(2): 311-326, February 2011. Springer (DOI: 10.1007/s00500-010-0547-5, PDF File, and Source Code in Microsoft Visual C++ 6.0).
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[25] R. Tinos and S. Yang. Self-adaptation of mutation distribution in evolution strategies for dynamic optimization problems. International Journal of Hybrid Intelligent Systems, 8(3): 155-168, June 2011. IOS Press (DOI: 10.3233/HIS-2011-0136 and PDF File).
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[26] R. Tinos and S. Yang. Use of the q-Gaussian mutation in evolutionary algorithms. Soft Computing, 15(8): 1523-1549, August 2011. Springer (DOI: 10.1007/s00500-010-0686-8, PDF File and Source Code in C++).
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[27] S. N. Jat and S. Yang. A hybrid genetic algorithm and tabu search approach for post enrolment course timetabling. Journal of Scheduling, 14(6): 617-637, December 2011. Springer (DOI: 10.1007/s10951-010-0202-0 and PDF File).
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[28] L. Liu, S. Yang, and D. Wang. Force-imitated particle swarm optimization using the near-neighbor effect for locating multiple optima. Information Sciences, 182(1): 139-155, January 2012. Elsevier (DOI: 10.1016/j.ins.2010.11.013 and PDF File).
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[29] C. Li, S. Yang, and T. T. Nguyen. A self-learning particle swarm optimizer for global optimization problems. IEEE Transactions on Systems, Man, and Cybernetics Part B: Cybernetics, 42(3): 627-646, June 2012. IEEE Press (DOI: 10.1109/TSMCB.2011.2171946 and PDF File).
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[30] H. Wang, S. Yang, W. H. Ip, and D. Wang. A memetic particle swarm optimization algorithm for dynamic multi-modal optimization problems. International Journal of Systems Science, 43(7): 1268-1283, July 2012. Taylor & Francis (DOI: 10.1080/00207721.2011.605966 and PDF File).
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[31] H. Wang, I.-K. Moon, S. Yang, and D. Wang. A memetic particle swarm optimization algorithm for multimodal optimization problems. Information Sciences, 197: 38-52, August 2012. Elsevier (DOI: 10.1016/j.ins.2012.02.016).
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[32] C. Li and S. Yang. A general framework of multi-population methods with clustering in undetectable dynamic environments. IEEE Transactions on Evolutionary Computation, 16(4): 556-577, August 2012. IEEE Press (DOI: 10.1109/TEVC.2011.2169966, PDF File, and Source Code in C++ with details on EAlib available here).
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[33] H. Cheng, S. Yang, and X. Wang. Immigrants enhanced multi-population genetic algorithms for dynamic shortest path routing problems in mobile ad hoc networks. Applied Artificial Intelligence, 26(7): 673-695, August 2012. Taylor & Francis (DOI: 10.1080/08839514.2012.701449).
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[34] T. T. Nguyen, S. Yang, and J. Branke. Evolutionary dynamic optimization: A survey of the state of the art. Swarm and Evolutionary Computation, 6: 1-24, October 2012. Elsevier (Invited survey paper, DOI: 10.1016/j.swevo.2012.05.001).
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[35] H. Cheng, S. Yang, and J. Cao. Dynamic genetic algorithms for the dynamic load balanced clustering problem in mobile ad hoc networks. Expert Systems with Applications, 40(4): 1381-1392, March 2013. Elsevier (DOI: 10.1016/j.eswa.2012.08.050).
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[36] W. Kong, T. Chai, S. Yang, and J. Ding. A hybrid evolutionary multiobjective optimization strategy for the dynamic power supply problem in magnesia grain manufacturing. Applied Soft Computing, 13(5): 2960-2969, March 2013. Elsevier (DOI: 10.1016/j.asoc.2012.02.025).
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[37] I. Korejo, S. Yang, K. Brohi, and Z.U.A. Khuhro. Multi-Population Methods with Adaptive Mutation for Multi-Modal Optimization Problems. International Journal on Soft Computing, Artificial Intelligence and Application, 2(2): 1-19, April 2013. Academy and Industry Research Collaboration Center (AIRCC) (DOI: 10.5121/ijscai.2013.2201).
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[38] M. Huang, Y. Cui, S. Yang, and X. Wang. Fourth party logistics routing problem with fuzzy duration time. International Journal of Production Economics, 145(1): 107-116, September 2013. Elsevier (DOI: 10.1016/j.ijpe.2013.03.007).
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[39] Y. Cui, M. Huang, S. Yang, L. H. Lee, and X. Wang. Fourth party logistics routing problem model with fuzzy duration time and cost discount. Knowledge-Based Systems, 50: 14-24, September, 2013. Elsevier (DOI: 10.1016/j.knosys.2013.04.020).
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[40] S. Yang, Y. Jiang, and T. T. Nguyen. Metaheuristics for dynamic combinatorial optimization problems. IMA Journal of Management Mathematics, 24(4): 451-480, October 2013. Oxford University Press (Invited survey paper, DOI: 10.1093/imaman/DPS021).
- 中国地质大学（武汉）校址：湖北省武汉市鲁磨路388号
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