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Evolutionary Algorithms for Dynamic Optimisation Problems:
Design, Analysis and Applications
Publications
Journal Papers
- L. Liu, S. Yang, and D. Wang. Particle swarm optimization with
composite particles in dynamic environments. Revised and resubmitted
to IEEE Trans on Evolutionary Computation, June 2008.
- H. Wang, D. Wang, and S. Yang. A memetic algorithm with adaptive
hill climbing strategy for dynamic optimization problems.
Accepted by Soft Computing, March 2008. Springer.
- H. Cheng, J. Cao, X. Wang, S. K. Das, and S. Yang.
Stability-aware multi-metric clustering in mobile ad hoc networks
with group mobility. Wireless Communications and Mobile Computing,
published online first: 21 Apr 2008. John Wiley & Sons, Ltd
(DOI: 10.1002/wcm.627).
- S. Yang and X. Yao. Population-based incremental learning with
associative memory for dynamic environments. IEEE
Transactions on Evolutionary Computation, 20 pages,
published online first: March 2008. IEEE Press
(DOI:
10.1109/TEVC.2007.913070).
- S. Yang. Genetic algorithms with memory and elitism based immigrants
in dynamic environments. Evolutionary Computation, 16(3), Fall 2008.
MIT Press.
- R. Tinos and S. Yang. A self-organizing random immigrants genetic
algorithm for dynamic optimization problems. Genetic Programming and
Evolvable Machines, 8(3): 255-286, September 2007. Springer
(DOI:
10.1007/s10710-007-9024-z).
- S. Yang and R. Tinos. A hybrid immigrants scheme for genetic algorithms
in dynamic environments. International Journal of Automation and
Computing, 4(3): 243-254, July 2007. Springer
(DOI:
10.1007/s11633-007-0243-9).
Conference Papers
- H. Cheng and S. Yang.
A Genetic-inspired joint multicast routing and channel assignment
algorithm in wireless mesh networks. To appear in
Proceedings of the 2008 UK Workshop on Computational Intelligence, 2008.
- C. Li and S. Yang.
An adaptive mutation operator for particle swarm optimization. To appear in
Proceedings of the 2008 UK Workshop on Computational Intelligence, 2008.
- H. Cheng, X. Wang, M. Huang, and S. Yang.
A review of personal communications services. To appear in
Proceedings of the 9th International Conference for Young
Computer Scientists, 2008. IEEE Press.
- C. Ji, Y. Zhang, M. Tong, and S. Yang. Particle filter with
swarm move for optimization. To appear in Proceedings of the 10th
International Conference on Parallel Problem Solving from Nature,
2008. Springer.
- C. Li and S. Yang. Fast multi-swarm optimization for dynamic
optimization problems. To appear in Proceedings of the 4th
International Conference on Natural Computation, 2008. IEEE Press.
- H. Richter and S. Yang. Learning in abstract memory schemes for dynamic
optimization. To appear in Proceedings of the 4th International Conference on Natural
Computation, 2008. IEEE Press.
- R. Tinos and S. Yang. Evolutionary programming with q-Gaussian mutation for
dynamic pptimization problems. Proceedings of the 2008 IEEE Congress on
Evolutionary Computation, pp. 1823-1830, 2008. IEEE Press.
- Y. Yan, H. Wang, D. Wang, S. Yang, and D. Z. Wang. A multi-agent based
evolutionary algorithm in non-stationary environments. Proceedings of the 2008
IEEE Congress on Evolutionary Computation, pp. 2972-2979, 2008. IEEE Press.
- S. Yang and R. Tinos. Hyper-selection in dynamic environments.
Proceedings of the 2008 IEEE Congress on Evolutionary Computation,
pp. 3184-3191, 2008. IEEE Press.
- H. Richter and S. Yang. Memory based on abstraction for dynamic fitness
functions. In Applications of Evolutionary Computing, LNCS 4974 ,
pp. 597-606, 2008. Berlin: Springer-Verlag
(DOI:
10.1007/978-3-540-78761-7_65).
- L. Liu, D. Wang, and S. Yang. Compound particle swarm optimization in
dynamic environments. In Applications of Evolutionary Computing, LNCS 4974,
pp. 617-626, 2008. Berlin: Springer-Verlag
(DOI:
10.1007/978-3-540-78761-7_67).
- R. Tinos and S. Yang. Self-adaptation of mutation distribution in
evolutionary algorithms. Proceedings of the 2007 IEEE Congress on
Evolutionary Computation, pp. 79-86, 2007. IEEE Press
(DOI:
10.1109/CEC.2007.4424457).
- R. Tinos and S. Yang. Continuous dynamic problem generators for
evolutionary algorithms. Proceedings of the 2007 IEEE Congress on
Evolutionary Computation, pp. 236-243, 2007. IEEE Press
(DOI:
10.1109/CEC.2007.4424477).
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