Recent advances in particle swarm optimization analysis and understanding

Engelbrecht & Cleghorn Particle Swarm Optimization GECCO’19, 13/7/2019 1 / 109 Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author(s). GECCO ’19 Companion, July 13–17, 2019, Prague, Czech Republic c © 2019 Copyright is held by the owner/author(s). ACM ISBN 978-1-4503-6748-6/19/07. doi:10.1145/3319619.3323368 Presenter Andries Engelbrecht

[1]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[2]  Andries Petrus Engelbrecht,et al.  Particle swarm convergence: An empirical investigation , 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

[3]  J. Kennedy,et al.  Neighborhood topologies in fully informed and best-of-neighborhood particle swarms , 2003, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[4]  E. Ozcan,et al.  Particle swarm optimization: surfing the waves , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[5]  Konstantinos E. Parsopoulos,et al.  UPSO: A Unified Particle Swarm Optimization Scheme , 2019, International Conference of Computational Methods in Sciences and Engineering 2004 (ICCMSE 2004).

[6]  Belinda Stapelberg,et al.  Particle Swarm Optimization: Stability Analysis using N-Informers under Arbitrary Coefficient Distributions , 2020, Swarm Evol. Comput..

[7]  Andries Petrus Engelbrecht,et al.  Fully informed particle swarm optimizer: Convergence analysis , 2015, 2015 IEEE Congress on Evolutionary Computation (CEC).

[8]  Rolf Wanka,et al.  Theoretical Analysis of Initial Particle Swarm Behavior , 2008, PPSN.

[9]  Andries Petrus Engelbrecht,et al.  Particle swarm optimization: Velocity initialization , 2012, 2012 IEEE Congress on Evolutionary Computation.

[10]  Andries Petrus Engelbrecht,et al.  Particle swarm optimizer: The impact of unstable particles on performance , 2016, 2016 IEEE Symposium Series on Computational Intelligence (SSCI).

[11]  Andries P. Engelbrecht,et al.  Multi-guide particle swarm optimization for multi-objective optimization: empirical and stability analysis , 2019, Swarm Intelligence.

[12]  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.

[13]  Andries Petrus Engelbrecht,et al.  Particle swarm variants: standardized convergence analysis , 2015, Swarm Intelligence.

[14]  Shiyuan Yang,et al.  Stochastic convergence analysis and parameter selection of the standard particle swarm optimization algorithm , 2007, Inf. Process. Lett..

[15]  Riccardo Poli,et al.  Mean and Variance of the Sampling Distribution of Particle Swarm Optimizers During Stagnation , 2009, IEEE Transactions on Evolutionary Computation.

[16]  Kalyan Veeramachaneni,et al.  Fitness-distance-ratio based particle swarm optimization , 2003, Proceedings of the 2003 IEEE Swarm Intelligence Symposium. SIS'03 (Cat. No.03EX706).

[17]  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).

[18]  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).

[19]  E. T. Oldewage,et al.  Degrees of stochasticity in particle swarm optimization , 2019, Swarm Intelligence.

[20]  A. P. Engelbrecht Particle Swarm Optimization: Iteration Strategies Revisited , 2013, 2013 BRICS Congress on Computational Intelligence and 11th Brazilian Congress on Computational Intelligence.

[21]  Andries Petrus Engelbrecht,et al.  A study of particle swarm optimization particle trajectories , 2006, Inf. Sci..

[22]  Zbigniew Michalewicz,et al.  Impacts of Coefficients on Movement Patterns in the Particle Swarm Optimization Algorithm , 2017, IEEE Transactions on Evolutionary Computation.

[23]  Christopher Wesley Cleghorn,et al.  Movement patterns of a particle swarm in high dimensional spaces , 2020, Inf. Sci..

[24]  D. Broomhead,et al.  Exact analysis of the sampling distribution for the canonical particle swarm optimiser and its convergence during stagnation , 2007, GECCO '07.

[25]  Andries Petrus Engelbrecht,et al.  The Importance of Component-Wise Stochasticity in Particle Swarm Optimization , 2018, ANTS Conference.

[26]  James Kennedy,et al.  Defining a Standard for Particle Swarm Optimization , 2007, 2007 IEEE Swarm Intelligence Symposium.

[27]  E. T. Oldewage,et al.  The perils of particle swarm optimization in high dimensional problem spaces , 2005 .

[28]  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.

[29]  Andries Petrus Engelbrecht,et al.  Boundary Constraint Handling Techniques for Particle Swarm Optimization in High Dimensional Problem Spaces , 2018, ANTS Conference.

[30]  Juan Luis Fernández-Martínez,et al.  Convergence and stochastic stability analysis of particle swarm optimization variants with generic parameter distributions , 2014 .

[31]  James Kennedy,et al.  The particle swarm: social adaptation of knowledge , 1997, Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97).

[32]  Christiaan Scheepers,et al.  Multi-guided particle swarm optimization : a multi-objective particle swarm optimizer , 2018 .

[33]  Christopher Wesley Cleghorn,et al.  Particle Swarm Optimization: Understanding Order-2 Stability Guarantees , 2019, EvoApplications.

[34]  Andries Petrus Engelbrecht,et al.  Particle swarm stability: a theoretical extension using the non-stagnate distribution assumption , 2018, Swarm Intelligence.

[35]  Ioan Cristian Trelea,et al.  The particle swarm optimization algorithm: convergence analysis and parameter selection , 2003, Inf. Process. Lett..