Variable mesh optimization for continuous optimization problems
暂无分享,去创建一个
Francisco Herrera | Rafael Bello | Daniel Molina | Amilkar Puris | F. Herrera | D. Molina | Rafael Bello | Amilkar Puris
[1] Francisco Herrera,et al. Tackling Real-Coded Genetic Algorithms: Operators and Tools for Behavioural Analysis , 1998, Artificial Intelligence Review.
[2] R. Iman,et al. Approximations of the critical region of the fbietkan statistic , 1980 .
[3] David J. Sheskin,et al. Handbook of Parametric and Nonparametric Statistical Procedures , 1997 .
[4] J. David Schaffer,et al. Proceedings of the third international conference on Genetic algorithms , 1989 .
[5] U Aickelin,et al. Handbook of metaheuristics (International series in operations research and management science) , 2005 .
[6] S. Holm. A Simple Sequentially Rejective Multiple Test Procedure , 1979 .
[7] Andries Petrus Engelbrecht,et al. Fundamentals of Computational Swarm Intelligence , 2005 .
[8] Rainer Storn,et al. Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..
[9] Gilbert Syswerda,et al. Uniform Crossover in Genetic Algorithms , 1989, ICGA.
[10] Janez Brest,et al. Performance comparison of self-adaptive and adaptive differential evolution algorithms , 2007, Soft Comput..
[11] Francisco Herrera,et al. Editorial Real coded genetic algorithms , 2005, Soft Comput..
[12] Kalyanmoy Deb,et al. Self-Adaptive Genetic Algorithms with Simulated Binary Crossover , 2001, Evolutionary Computation.
[13] F. Wilcoxon. Individual Comparisons by Ranking Methods , 1945 .
[14] Yue Shi,et al. A modified particle swarm optimizer , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).
[15] C. Fernandes,et al. A study on non-random mating and varying population size in genetic algorithms using a royal road function , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).
[16] F. Glover,et al. Handbook of Metaheuristics , 2019, International Series in Operations Research & Management Science.
[17] Francisco Herrera,et al. Editorial scalability of evolutionary algorithms and other metaheuristics for large-scale continuous optimization problems , 2011, Soft Comput..
[18] James Kennedy,et al. Particle swarm optimization , 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.
[19] Francisco Herrera,et al. A study of statistical techniques and performance measures for genetics-based machine learning: accuracy and interpretability , 2009, Soft Comput..
[20] Jing J. Liang,et al. Problem Definitions and Evaluation Criteria for the CEC 2005 Special Session on Real-Parameter Optimization , 2005 .
[21] Zbigniew Michalewicz,et al. Feature cluster on adaptation of discrete metaheuristics to continuous optimization , 2008, Eur. J. Oper. Res..
[22] S. Rahnamayan,et al. Solving large scale optimization problems by opposition-based differential evolution (ODE) , 2008 .
[23] Francisco Herrera,et al. A study on the use of non-parametric tests for analyzing the evolutionary algorithms’ behaviour: a case study on the CEC’2005 Special Session on Real Parameter Optimization , 2009, J. Heuristics.
[24] Rafael Martí,et al. Scatter Search: Diseño Básico y Estrategias avanzadas , 2002, Inteligencia Artif..
[25] Francisco Herrera,et al. A taxonomy for the crossover operator for real‐coded genetic algorithms: An experimental study , 2003, Int. J. Intell. Syst..