APS 9: an improved adaptive population-based simplex method for real-world engineering optimization problems
暂无分享,去创建一个
[1] Ponnuthurai N. Suganthan,et al. Modified differential evolution with local search algorithm for real world optimization , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).
[2] Xavier Blasco Ferragud,et al. Hybrid DE algorithm with adaptive crossover operator for solving real-world numerical optimization problems , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).
[3] Mahamed G. H. Omran,et al. An Adaptive Population-based Simplex Method for Continuous Optimization , 2016, Int. J. Swarm Intell. Res..
[4] Maurice Clerc,et al. Standard Particle Swarm Optimisation , 2012 .
[5] R. Glynn,et al. The Wilcoxon Signed Rank Test for Paired Comparisons of Clustered Data , 2006, Biometrics.
[6] Tapabrata Ray,et al. An adaptive differential evolution algorithm and its performance on real world optimization problems , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).
[7] Jurij Silc,et al. The Continuous Differential Ant-Stigmergy Algorithm applied to real-world optimization problems , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).
[8] Ajith Abraham,et al. Self adaptive cluster based and weed inspired differential evolution algorithm for real world optimization , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).
[9] Nikolaus Hansen,et al. The CMA Evolution Strategy: A Comparing Review , 2006, Towards a New Evolutionary Computation.
[10] John A. Nelder,et al. A Simplex Method for Function Minimization , 1965, Comput. J..
[11] Qingfu Zhang,et al. Enhancing the search ability of differential evolution through orthogonal crossover , 2012, Inf. Sci..
[12] Antonio LaTorre,et al. Benchmarking a hybrid DE-RHC algorithm on real world problems , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).
[13] Changhe Li,et al. A Self-Learning Particle Swarm Optimizer for Global Optimization Problems , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[14] Ruhul A. Sarker,et al. Differential evolution with multiple strategies for solving CEC2011 real-world numerical optimization problems , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).
[15] Tapabrata Ray,et al. Performance of a hybrid EA-DE-memetic algorithm on CEC 2011 real world optimization problems , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).
[16] Mahamed G. H. Omran,et al. The Adaptive Population-based Simplex method , 2015, 2015 Fifth International Conference on Digital Information Processing and Communications (ICDIPC).
[17] Tapabrata Ray,et al. How does the good old Genetic Algorithm fare at real world optimization? , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).
[18] Ruhul A. Sarker,et al. GA with a new multi-parent crossover for solving IEEE-CEC2011 competition problems , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).
[19] M. Friedman. A Comparison of Alternative Tests of Significance for the Problem of $m$ Rankings , 1940 .
[20] Bin Li,et al. Estimation of distribution and differential evolution cooperation for real-world numerical optimization problems , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).
[21] P. N. Suganthan,et al. Problem Definitions and Evaluation Criteria for CEC 2011 Competition on Testing Evolutionary Algorithms on Real World Optimization Problems , 2011 .
[22] L. Darrell Whitley,et al. The dispersion metric and the CMA evolution strategy , 2006, GECCO.
[23] Alex S. Fukunaga,et al. Evaluating the performance of SHADE on CEC 2013 benchmark problems , 2013, 2013 IEEE Congress on Evolutionary Computation.
[24] Shaoliang Zhang,et al. Some modifications of low-dimensional simplex evolution and their convergence , 2013, Optim. Methods Softw..
[25] Jing J. Liang,et al. Problem Definitions and Evaluation Criteria for the CEC 2005 Special Session on Real-Parameter Optimization , 2005 .
[26] Ruhul A. Sarker,et al. Two-phase differential evolution framework for solving optimization problems , 2016, 2016 IEEE Symposium Series on Computational Intelligence (SSCI).
[27] Kalyanmoy Deb,et al. Modified SBX and adaptive mutation for real world single objective optimization , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).
[28] 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.
[29] Ponnuthurai N. Suganthan,et al. Ensemble differential evolution algorithm for CEC2011 problems , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).