Particle Swarm Optimization for Single Objective Continuous Space Problems: A Review
暂无分享,去创建一个
[1] John W. Chinneck,et al. Constraint consensus concentration for identifying disjoint feasible regions in nonlinear programmes , 2013, Optim. Methods Softw..
[2] Francisco Herrera,et al. A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms , 2011, Swarm Evol. Comput..
[3] Anne Auger,et al. Experimental Comparisons of Derivative Free Optimization Algorithms , 2009, SEA.
[4] Cheng-Yan Kao,et al. Applying Family Competition to Evolution Strategies for Constrained Optimization , 1997, Evolutionary Programming.
[5] 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).
[6] M. S. Voss,et al. Principal component particle swarm optimization: a step towards topological swarm intelligence , 2005, 2005 IEEE Congress on Evolutionary Computation.
[7] Zbigniew Michalewicz,et al. Evolutionary Computation at the Edge of Feasibility , 1996, PPSN.
[8] Jun Zhang,et al. Adaptive Particle Swarm Optimization , 2008, ANTS Conference.
[9] M. Senthil Arumugam,et al. A novel and effective particle swarm optimization like algorithm with extrapolation technique , 2009, Appl. Soft Comput..
[10] Andries Petrus Engelbrecht,et al. Particle swarm variants: standardized convergence analysis , 2015, Swarm Intelligence.
[11] Xiaodong Li,et al. Cooperative Co-Evolution With Differential Grouping for Large Scale Optimization , 2014, IEEE Transactions on Evolutionary Computation.
[12] M. Senthil Arumugam,et al. A new and improved version of particle swarm optimization algorithm with global–local best parameters , 2008, Knowledge and Information Systems.
[13] Per Kristian Lehre,et al. Finite First Hitting Time versus Stochastic Convergence in Particle Swarm Optimisation , 2011, ArXiv.
[14] Cleve B. Moler,et al. Nineteen Dubious Ways to Compute the Exponential of a Matrix, Twenty-Five Years Later , 1978, SIAM Rev..
[15] Ming-Feng Yeh,et al. Grey particle swarm optimization , 2012, Appl. Soft Comput..
[16] Ling Wang,et al. An effective co-evolutionary particle swarm optimization for constrained engineering design problems , 2007, Eng. Appl. Artif. Intell..
[17] Guo-Chang Gu,et al. Research on particle swarm optimization: a review , 2004, Proceedings of 2004 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.04EX826).
[18] Zbigniew Michalewicz,et al. SPSO 2011: analysis of stability; local convergence; and rotation sensitivity , 2014, GECCO.
[19] Xin Yao,et al. From an individual to a population: an analysis of the first hitting time of population-based evolutionary algorithms , 2002, IEEE Trans. Evol. Comput..
[20] J. Kennedy,et al. Population structure and particle swarm performance , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).
[21] M. Clerc,et al. Particle Swarm Optimization , 2006 .
[22] Carl Tim Kelley,et al. Iterative methods for optimization , 1999, Frontiers in applied mathematics.
[23] 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.
[24] Liyan Zhang,et al. Empirical study of particle swarm optimizer with an increasing inertia weight , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..
[25] Andries Petrus Engelbrecht,et al. Quantifying ruggedness of continuous landscapes using entropy , 2009, 2009 IEEE Congress on Evolutionary Computation.
[26] Andries Petrus Engelbrecht,et al. Particle swarm convergence: An empirical investigation , 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).
[27] Zbigniew Michalewicz,et al. Boundary Operators for Constrained Parameter Optimization Problems , 1997, ICGA.
[28] Zbigniew Michalewicz,et al. Evolutionary Algorithms for Constrained Parameter Optimization Problems , 1996, Evolutionary Computation.
[29] Chukwudi Anyakoha,et al. A review of particle swarm optimization. Part II: hybridisation, combinatorial, multicriteria and constrained optimization, and indicative applications , 2008, Natural Computing.
[30] Thomas Stützle,et al. Towards incremental social learning in optimization and multiagent systems , 2008, GECCO '08.
[31] Andries Petrus Engelbrecht,et al. A Cooperative approach to particle swarm optimization , 2004, IEEE Transactions on Evolutionary Computation.
[32] Rainer Storn,et al. Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..
[33] Anan Nimtawat,et al. Simple Particle Swarm Optimization for Solving Beam-Slab Layout Design Problems , 2011 .
[34] Derek T. Green,et al. Biases in Particle Swarm Optimization , 2010 .
[35] Thomas Stützle,et al. Frankenstein's PSO: A Composite Particle Swarm Optimization Algorithm , 2009, IEEE Transactions on Evolutionary Computation.
[36] Yang Tang,et al. Feedback learning particle swarm optimization , 2011, Appl. Soft Comput..
[37] Erwie Zahara,et al. A hybrid genetic algorithm and particle swarm optimization for multimodal functions , 2008, Appl. Soft Comput..
[38] Juan Luis Fernández-Martínez,et al. Convergence and stochastic stability analysis of particle swarm optimization variants with generic parameter distributions , 2014 .
[39] XI FachbereichInformatik. Finite Markov Chain Results in Evolutionary Computation: a Tour D'horizon , 1998 .
[40] Zbigniew Michalewicz,et al. GENOCOP: a genetic algorithm for numerical optimization problems with linear constraints , 1996, CACM.
[41] Mark E. J. Newman,et al. Structure and Dynamics of Networks , 2009 .
[42] Nikolaus Hansen,et al. The CMA Evolution Strategy: A Comparing Review , 2006, Towards a New Evolutionary Computation.
[43] Hans-Paul Schwefel,et al. Evolution strategies – A comprehensive introduction , 2002, Natural Computing.
[44] Russell C. Eberhart,et al. Parameter Selection in Particle Swarm Optimization , 1998, Evolutionary Programming.
[45] Massimiliano Kaucic. A multi-start opposition-based particle swarm optimization algorithm with adaptive velocity for bound constrained global optimization , 2013, J. Glob. Optim..
[46] M. Clerc,et al. The swarm and the queen: towards a deterministic and adaptive particle swarm optimization , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).
[47] Jing J. Liang,et al. Comprehensive learning particle swarm optimizer for global optimization of multimodal functions , 2006, IEEE Transactions on Evolutionary Computation.
[48] Xin Yao,et al. Continuous Dynamic Constrained Optimization—The Challenges , 2012, IEEE Transactions on Evolutionary Computation.
[49] Riccardo Poli,et al. Theoretical derivation, analysis and empirical evaluation of a simpler Particle Swarm Optimiser , 2007, 2007 IEEE Congress on Evolutionary Computation.
[50] Margaret J. Robertson,et al. Design and Analysis of Experiments , 2006, Handbook of statistics.
[51] Mohammad Mehdi Ebadzadeh,et al. A novel particle swarm optimization algorithm with adaptive inertia weight , 2011, Appl. Soft Comput..
[52] Andries Petrus Engelbrecht,et al. A Convergence Proof for the Particle Swarm Optimiser , 2010, Fundam. Informaticae.
[53] Jens Jägersküpper,et al. Design and Management of Complex Technical Processes and Systems by means of Computational Intelligence Methods General Lower Bounds for Randomized Direct Search with Isotropic Sampling , 2008 .
[54] P. N. Suganthan,et al. A dynamic neighborhood learning based particle swarm optimizer for global numerical optimization , 2012, Inf. Sci..
[55] Günter Rudolph,et al. Theory of Evolutionary Algorithms: A Bird's Eye View , 1999, Theor. Comput. Sci..
[56] Zbigniew Michalewicz,et al. Stability Analysis of the Particle Swarm Optimization Without Stagnation Assumption , 2016, IEEE Transactions on Evolutionary Computation.
[57] Zbigniew Michalewicz,et al. A locally convergent rotationally invariant particle swarm optimization algorithm , 2014, Swarm Intelligence.
[58] Andries Petrus Engelbrecht,et al. Particle Swarm Convergence: Standardized Analysis and Topological Influence , 2014, ANTS Conference.
[59] Nikolaus Hansen,et al. Adapting arbitrary normal mutation distributions in evolution strategies: the covariance matrix adaptation , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.
[60] D. Agrafiotis,et al. Feature selection for structure-activity correlation using binary particle swarms. , 2002, Journal of medicinal chemistry.
[61] J. Deng,et al. Introduction to Grey system theory , 1989 .
[62] Zbigniew Michalewicz,et al. Locating Potentially Disjoint Feasible Regions of a Search Space with a Particle Swarm Optimizer , 2015 .
[63] Qunfeng Liu,et al. Order-2 Stability Analysis of Particle Swarm Optimization , 2015, Evolutionary Computation.
[64] Maurice Clerc,et al. Performance evaluation of TRIBES, an adaptive particle swarm optimization algorithm , 2009, Swarm Intelligence.
[65] Michael N. Vrahatis,et al. Recent approaches to global optimization problems through Particle Swarm Optimization , 2002, Natural Computing.
[66] Duncan J. Watts,et al. The Structure and Dynamics of Networks: (Princeton Studies in Complexity) , 2006 .
[67] Xin Yao,et al. Evolving artificial neural networks , 1999, Proc. IEEE.
[68] A. Groenwold,et al. Comparison of linear and classical velocity update rules in particle swarm optimization: notes on scale and frame invariance , 2007 .
[69] Zhigang Shang,et al. Coevolutionary Comprehensive Learning Particle Swarm Optimizer , 2010, IEEE Congress on Evolutionary Computation.
[70] Ioan Cristian Trelea,et al. The particle swarm optimization algorithm: convergence analysis and parameter selection , 2003, Inf. Process. Lett..
[71] Peter J. Angeline,et al. Evolutionary Optimization Versus Particle Swarm Optimization: Philosophy and Performance Differences , 1998, Evolutionary Programming.
[72] Esperanza García Gonzalo,et al. Convergence and stochastic stability analysis of particle swarm optimization variants with generic parameter distributions , 2014, Appl. Math. Comput..
[73] Frans van den Bergh,et al. An analysis of particle swarm optimizers , 2002 .
[74] N. Hansen,et al. PSO Facing Non-Separable and Ill-Conditioned Problems , 2008 .
[75] Rolf Wanka,et al. Theoretical Analysis of Initial Particle Swarm Behavior , 2008, PPSN.
[76] Hassan M. Emara,et al. Adaptive Clubs-based Particle Swarm Optimization , 2009, 2009 American Control Conference.
[77] R. Salomon. Re-evaluating genetic algorithm performance under coordinate rotation of benchmark functions. A survey of some theoretical and practical aspects of genetic algorithms. , 1996, Bio Systems.
[78] Michael N. Vrahatis,et al. On the computation of all global minimizers through particle swarm optimization , 2004, IEEE Transactions on Evolutionary Computation.
[79] Ruhul A. Sarker,et al. Particle Swarm Optimizer for constrained optimization , 2013, 2013 IEEE Congress on Evolutionary Computation.
[80] Christian L. Müller,et al. Particle Swarm CMA Evolution Strategy for the optimization of multi-funnel landscapes , 2009, 2009 IEEE Congress on Evolutionary Computation.
[81] James Kennedy,et al. Bare bones particle swarms , 2003, Proceedings of the 2003 IEEE Swarm Intelligence Symposium. SIS'03 (Cat. No.03EX706).
[82] Michael N. Vrahatis,et al. Particle Swarm Optimization Method for Constrained Optimization Problems , 2002 .
[83] Jeng-Shyang Pan,et al. An improved vector particle swarm optimization for constrained optimization problems , 2011, Inf. Sci..
[84] Thomas Stützle,et al. Incremental Social Learning in Particle Swarms , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[85] Vishnu Prasad,et al. Economic dispatch using particle swarm optimization: A review , 2009 .
[86] Jun Zhang,et al. Orthogonal Learning Particle Swarm Optimization , 2009, IEEE Transactions on Evolutionary Computation.
[87] Jing J. Liang,et al. Problem Definitions and Evaluation Criteria for the CEC 2005 Special Session on Real-Parameter Optimization , 2005 .
[88] Xiang Li,et al. A hybrid particle swarm with a time-adaptive topology for constrained optimization , 2014, Swarm and Evolutionary Computation.
[89] Russell C. Eberhart,et al. Recent advances in particle swarm , 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).
[90] Carlos A. Coello Coello,et al. Use of a self-adaptive penalty approach for engineering optimization problems , 2000 .
[91] Zbigniew Michalewicz,et al. GAVaPS-a genetic algorithm with varying population size , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.
[92] Ajith Abraham,et al. On stability and convergence of the population-dynamics in differential evolution , 2009, AI Commun..
[93] Zbigniew Michalewicz,et al. Beyond the Edge of Feasibility: Analysis of Bottlenecks , 2014, SEAL.
[94] E. Ozcan,et al. Particle swarm optimization: surfing the waves , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).
[95] Chenggong Zhang,et al. Scale-free fully informed particle swarm optimization algorithm , 2011, Inf. Sci..
[96] Carlos A. Coello Coello,et al. A constraint-handling mechanism for particle swarm optimization , 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).
[97] Anne Auger,et al. Impacts of invariance in search: When CMA-ES and PSO face ill-conditioned and non-separable problems , 2011, Appl. Soft Comput..
[98] Andries Petrus Engelbrecht,et al. Particle Swarms for Linearly Constrained Optimisation , 2007, Fundam. Informaticae.
[99] Richard J. Duro,et al. Real-Valued Multimodal Fitness Landscape Characterization for Evolution , 2010, ICONIP.
[100] Andries Petrus Engelbrecht,et al. A generalized theoretical deterministic particle swarm model , 2014, Swarm Intelligence.
[101] Andries Petrus Engelbrecht,et al. Fundamentals of Computational Swarm Intelligence , 2005 .
[102] Zbigniew Michalewicz,et al. On the edge of feasibility: A case study of the particle swarm optimizer , 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).
[103] M. Jiang,et al. Particle Swarm Optimization - Stochastic Trajectory Analysis and Parameter Selection , 2007 .
[104] G. Unter Rudolph. Local Convergence Rates of Simple Evolutionary Algorithms with Cauchy Mutations , 1998 .
[105] Chukwudi Anyakoha,et al. A review of particle swarm optimization. Part I: background and development , 2007, Natural Computing.
[106] Bijaya K. Panigrahi,et al. An inertia-adaptive particle swarm system with particle mobility factor for improved global optimization , 2010, Neural Computing and Applications.
[107] Andrew Lim,et al. Example-based learning particle swarm optimization for continuous optimization , 2012, Information Sciences.
[108] S. Halgamuge,et al. A comparison of constraint-handling methods for the application of particle swarm optimization to constrained nonlinear optimization problems , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..
[109] Jürgen Branke,et al. Experimental Analysis of Bound Handling Techniques in Particle Swarm Optimization , 2013, IEEE Transactions on Evolutionary Computation.
[110] B. Alatas,et al. Chaos embedded particle swarm optimization algorithms , 2009 .
[111] Carsten Witt,et al. Why standard particle swarm optimisers elude a theoretical runtime analysis , 2009, FOGA '09.
[112] Maurice Clerc,et al. The particle swarm - explosion, stability, and convergence in a multidimensional complex space , 2002, IEEE Trans. Evol. Comput..
[113] Ruhul A. Sarker,et al. Memetic multi-topology particle swarm optimizer for constrained optimization , 2012, 2012 IEEE Congress on Evolutionary Computation.
[114] Riccardo Poli,et al. Particle swarm optimization , 1995, Swarm Intelligence.
[115] Rolf Wanka,et al. Particle swarm optimization almost surely finds local optima , 2013, GECCO '13.
[116] L. Trefethen,et al. Numerical linear algebra , 1997 .
[117] Junyan Wang,et al. Nonlinear Inertia Weight Variation for Dynamic Adaptation in Particle Swarm Optimization , 2011, ICSI.
[118] Tim Blackwell,et al. A Study of Collapse in Bare Bones Particle Swarm Optimization , 2012, IEEE Transactions on Evolutionary Computation.
[119] Shiyuan Yang,et al. Stochastic convergence analysis and parameter selection of the standard particle swarm optimization algorithm , 2007, Inf. Process. Lett..
[120] Saman K. Halgamuge,et al. Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients , 2004, IEEE Transactions on Evolutionary Computation.
[121] Riccardo Poli,et al. Mean and Variance of the Sampling Distribution of Particle Swarm Optimizers During Stagnation , 2009, IEEE Transactions on Evolutionary Computation.
[122] Albert-László Barabási,et al. Statistical mechanics of complex networks , 2001, ArXiv.
[123] Zhao Xinchao. A perturbed particle swarm algorithm for numerical optimization , 2010 .
[124] ChunXia Zhao,et al. Particle swarm optimization with adaptive population size and its application , 2009, Appl. Soft Comput..
[125] Y. Pang. Expected number of steps of a random optimization method , 1985 .
[126] Shu-Cherng Fang,et al. On the Convergence of a Population-Based Global Optimization Algorithm , 2004, J. Glob. Optim..
[127] Russell C. Eberhart,et al. Solving Constrained Nonlinear Optimization Problems with Particle Swarm Optimization , 2002 .
[128] Andries Petrus Engelbrecht,et al. Particle swarm optimization: Velocity initialization , 2012, 2012 IEEE Congress on Evolutionary Computation.
[129] Giovanni Fasano,et al. Dynamic analysis for the selection of parameters and initial population, in particle swarm optimization , 2010, J. Glob. Optim..
[130] Zbigniew Michalewicz,et al. A Survey of Constraint Handling Techniques in Evolutionary Computation Methods , 1995 .
[131] 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).
[132] N. Hansen. Invariance, Self-adaptation and Correlated Mutations in Evolution Strategies Invariance, Self-adaptation and Correlated Mutations in Evolution Strategies , 2000 .
[133] James Kennedy,et al. Small worlds and mega-minds: effects of neighborhood topology on particle swarm performance , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).
[134] Xiang Li,et al. A hybrid particle swarm with velocity mutation for constraint optimization problems , 2013, GECCO '13.
[135] R. Eberhart,et al. Comparing inertia weights and constriction factors in particle swarm optimization , 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).
[136] Zbigniew Michalewicz,et al. A fast particle swarm optimization algorithm for the multidimensional knapsack problem , 2012, 2012 IEEE Congress on Evolutionary Computation.
[137] Yu Wang,et al. Self-adaptive learning based particle swarm optimization , 2011, Inf. Sci..
[138] Andries Petrus Engelbrecht,et al. A new particle swarm optimiser for linearly constrained optimisation , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..
[139] Tetsuyuki Takahama,et al. Constrained Optimization by the alpha Constrained Particle Swarm Optimizer , 2005, J. Adv. Comput. Intell. Intell. Informatics.
[140] Daniel N. Wilke,et al. Analysis of the particle swarm optimization algorithm , 2007 .
[141] R. Eberhart,et al. Fuzzy adaptive particle swarm optimization , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).
[142] Jun Zhang,et al. Small-world particle swarm optimization with topology adaptation , 2013, GECCO '13.
[143] A. P. Engelbrecht,et al. Particle Swarm Optimization: Global Best or Local Best? , 2013, 2013 BRICS Congress on Computational Intelligence and 11th Brazilian Congress on Computational Intelligence.
[144] Zbigniew Michalewicz,et al. An analysis of the velocity updating rule of the particle swarm optimization algorithm , 2014, Journal of Heuristics.
[145] Jun Zhang,et al. A Novel Set-Based Particle Swarm Optimization Method for Discrete Optimization Problems , 2010, IEEE Transactions on Evolutionary Computation.
[146] Riccardo Poli,et al. Particle Swarm Optimisation , 2011 .
[147] A. Engelbrecht,et al. A new locally convergent particle swarm optimiser , 2002, IEEE International Conference on Systems, Man and Cybernetics.
[148] David J. Sheskin,et al. Handbook of Parametric and Nonparametric Statistical Procedures , 1997 .
[149] Roger J.-B. Wets,et al. Minimization by Random Search Techniques , 1981, Math. Oper. Res..
[150] Saral Mukherjee,et al. Unified Concept of Bottleneck , 2006 .
[151] M. N. Vrahatis,et al. A New Unconstrained Optimization Method for Imprecise Function and Gradient Values , 1996 .
[152] Hui Wang,et al. Diversity enhanced particle swarm optimization with neighborhood search , 2013, Inf. Sci..
[153] N. Baba. Convergence of a random optimization method for constrained optimization problems , 1981 .
[154] Martin Middendorf,et al. A hierarchical particle swarm optimizer and its adaptive variant , 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[155] Teresa Wu,et al. An intelligent augmentation of particle swarm optimization with multiple adaptive methods , 2012, Inf. Sci..
[156] Andries Petrus Engelbrecht,et al. A study of particle swarm optimization particle trajectories , 2006, Inf. Sci..
[157] Rolf Wanka,et al. Particle Swarm Optimization in High-Dimensional Bounded Search Spaces , 2007, 2007 IEEE Swarm Intelligence Symposium.
[158] Riccardo Poli,et al. Analysis of the publications on the applications of particle swarm optimisation , 2008 .
[159] Rui Zou,et al. Particle Swarm Optimization-Based Source Seeking , 2015, IEEE Transactions on Automation Science and Engineering.
[160] James Kennedy,et al. Defining a Standard for Particle Swarm Optimization , 2007, 2007 IEEE Swarm Intelligence Symposium.
[161] Anne Auger,et al. Empirical comparisons of several derivative free optimization algorithms , 2009 .
[162] Shang-Jeng Tsai,et al. Efficient Population Utilization Strategy for Particle Swarm Optimizer , 2009, IEEE Trans. Syst. Man Cybern. Part B.
[163] Maurice Clerc,et al. Standard Particle Swarm Optimisation , 2012 .
[164] Zbigniew Michalewicz,et al. Parameter Control in Evolutionary Algorithms , 2007, Parameter Setting in Evolutionary Algorithms.
[165] José Neves,et al. The fully informed particle swarm: simpler, maybe better , 2004, IEEE Transactions on Evolutionary Computation.
[166] Russell C. Eberhart,et al. Tracking and optimizing dynamic systems with particle swarms , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).
[167] Zbigniew Michalewicz,et al. Analysis of Stability, Local Convergence, and Transformation Sensitivity of a Variant of the Particle Swarm Optimization Algorithm , 2016, IEEE Transactions on Evolutionary Computation.
[168] T. Krink,et al. Particle swarm optimisation with spatial particle extension , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).
[169] P. Suganthan,et al. Problem Definitions and Evaluation Criteria for the CEC 2010 Competition on Constrained Real- Parameter Optimization , 2010 .