The sensitivity of single objective optimization algorithm control parameter values under different computational constraints
暂无分享,去创建一个
[1] Andries Petrus Engelbrecht,et al. Fundamentals of Computational Swarm Intelligence , 2005 .
[2] Russell C. Eberhart,et al. Parameter Selection in Particle Swarm Optimization , 1998, Evolutionary Programming.
[3] A. E. Eiben,et al. Comparing parameter tuning methods for evolutionary algorithms , 2009, 2009 IEEE Congress on Evolutionary Computation.
[4] Qingfu Zhang,et al. Differential Evolution With Composite Trial Vector Generation Strategies and Control Parameters , 2011, IEEE Transactions on Evolutionary Computation.
[5] Saku Kukkonen,et al. Real-parameter optimization with differential evolution , 2005, 2005 IEEE Congress on Evolutionary Computation.
[6] Russell C. Eberhart,et al. A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.
[7] Andries Petrus Engelbrecht,et al. A Cooperative approach to particle swarm optimization , 2004, IEEE Transactions on Evolutionary Computation.
[8] Rainer Storn,et al. Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..
[9] John J. Grefenstette,et al. Optimization of Control Parameters for Genetic Algorithms , 1986, IEEE Transactions on Systems, Man, and Cybernetics.
[10] M. E. H. Pedersen,et al. Tuning & simplifying heuristical optimization , 2010 .
[11] David H. Wolpert,et al. No free lunch theorems for optimization , 1997, IEEE Trans. Evol. Comput..
[12] Maurice Clerc,et al. The particle swarm - explosion, stability, and convergence in a multidimensional complex space , 2002, IEEE Trans. Evol. Comput..
[13] Schalk Kok,et al. Locating and Characterizing the Stationary Points of the Extended Rosenbrock Function , 2009, Evolutionary Computation.