Particle swarm optimization algorithm: An overview

Wang, Dongshu; Tan, Dapei; Liu, Lei

doi:10.1007/s00500-016-2474-6

Cited by 3,343Metaheuristic Optimization Algorithms ResearchDistributed Control Multi-Agent SystemsAntenna Design and Optimization

Particle swarm optimization algorithm: An overview

Wang, Dongshu, Tan, Dapei, Liu, Lei·2018·Soft Computing

DOI 10.1007/s00500-016-2474-6

Open this paper in CoChat — free account

Integrity signals

Registry

Crossref · 10.1007/s00500-016-2474-6

Cites

194 of 194 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Particle swarm optimization
Kennedy, J., & Eberhart, R. (2002) · Proceedings of ICNN'95 - International Conference on Neural Networks · doi:10.1109/icnn.1995.488968 · Cited by 58,192 · see citing works
A fast and elitist multiobjective genetic algorithm: NSGA-II
Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. (2002) · IEEE Transactions on Evolutionary Computation · doi:10.1109/4235.996017 · Cited by 50,053 · see citing works
Particle swarm optimization: An overview
Poli, R., Kennedy, J., & Blackwell, T. (2007) · Swarm Intelligence · doi:10.1007/s11721-007-0002-0 · Cited by 21,101 · see citing works
A new optimizer using particle swarm theory
Eberhart, R., & Kennedy, J. (2002) · MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science · doi:10.1109/mhs.1995.494215 · Cited by 14,979 · see citing works
No free lunch theorems for optimization
Wolpert, D. H., & Macready, W. G. (1997) · IEEE Transactions on Evolutionary Computation · doi:10.1109/4235.585893 · Cited by 14,237 · see citing works
A modified particle swarm optimizer
Shi, Y., & Eberhart, R. (1998) · 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360) · doi:10.1109/icec.1998.699146 · Cited by 11,497 · see citing works
The particle swarm - explosion, stability, and convergence in a multidimensional complex space
Clerc, M., & Kennedy, J. (2002) · IEEE Transactions on Evolutionary Computation · doi:10.1109/4235.985692 · Cited by 9,053 · see citing works
Flocks, herds and schools: A distributed behavioral model
Reynolds, C. W. (1987) · ACM SIGGRAPH Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH) · doi:10.1145/37401.37406 · Cited by 7,795 · see citing works
Flocks, herds and schools: A distributed behavioral model
Reynolds, C. W. (1987) · ACM SIGGRAPH Computer Graphics · doi:10.1145/37402.37406 · Cited by 5,148 · see citing works
Handling multiple objectives with particle swarm optimization
Coello, C. A. C., Toscano‐Pulido, G., & Lechuga, M. S. (2004) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2004.826067 · Cited by 4,493 · see citing works
Particle swarm optimization: developments, applications and resources
Eberhart, & Shi, Y. (2001) · Congress on Evolutionary Computation · doi:10.1109/cec.2001.934374 · Cited by 4,332 · see citing works
Comprehensive learning particle swarm optimizer for global optimization of multimodal functions
Liang, J., Qin, A. K., Suganthan, P. N., & Baskar, S. S. (2006) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2005.857610 · Cited by 3,755 · see citing works
Self-Organizing Hierarchical Particle Swarm Optimizer With Time-Varying Acceleration Coefficients
Ratnaweera, A., Halgamuge, S. K., & Watson, H. C. (2004) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2004.826071 · Cited by 3,050 · see citing works
Comparing inertia weights and constriction factors in particle swarm optimization
Eberhart, R. C., & Shi, Y. (2002) · IEEE Congress on Evolutionary Computation (CEC) · doi:10.1109/cec.2000.870279 · Cited by 2,969 · see citing works
The particle swarm optimization algorithm: convergence analysis and parameter selection
Trelea, I.-C. (2003) · Information Processing Letters · doi:10.1016/s0020-0190(02)00447-7 · Cited by 2,656 · see citing works
Multiple Objective Optimization with Vector Evaluated Genetic Algorithms
Schaffer, J. D. (1985) · international conference on Genetic algorithms · Cited by 2,656 · see citing works
Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems
del Valle, Y., Venayagamoorthy, G. K., Mohagheghi, S., Hernández, J. C., & Harley, R. G. (2008) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2007.896686 · Cited by 2,277 · see citing works
Particle swarm optimization in electromagnetics
Robinson, J. T., & Rahmat‐Samii, Y. (2004) · IEEE Transactions on Antennas and Propagation · doi:10.1109/tap.2004.823969 · Cited by 2,266 · see citing works
A Cooperative Approach to Particle Swarm Optimization
vandenBergh, F., & Engelbrecht, A. P. (2004) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2004.826069 · Cited by 2,122 · see citing works
Adaptive Particle Swarm Optimization
Zhan, Z., Zhang, J., Li, Y., & Chung, H. S.-H. (2009) · IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) · doi:10.1109/tsmcb.2009.2015956 · Cited by 2,106 · see citing works
The Fully Informed Particle Swarm: Simpler, Maybe Better
Mendes, R., Kennedy, J., & Neves, J. (2004) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2004.826074 · Cited by 1,747 · see citing works
The swarm and the queen: towards a deterministic and adaptive particle swarm optimization
Clerc, M. (2003) · IEEE Congress on Evolutionary Computation (CEC) · doi:10.1109/cec.1999.785513 · Cited by 1,697 · see citing works
Population structure and particle swarm performance
Kennedy, J., & Mendes, R. (2003) · IEEE Congress on Evolutionary Computation (CEC) · doi:10.1109/cec.2002.1004493 · Cited by 1,593 · see citing works
An analysis of particle swarm optimizers
van den Bergh, F., & Engelbrecht, A. P. (2002) · UpSpace Institutional Repository (University of Pretoria) · Cited by 1,421 · see citing works
A study of particle swarm optimization particle trajectories
VANDENBERGH, F., & Engelbrecht, A. P. (2005) · Information Sciences · doi:10.1016/j.ins.2005.02.003 · Cited by 1,406 · see citing works
Recent approaches to global optimization problems through Particle Swarm Optimization
Parsopoulos, K. E., & Vrahatis, M. N. (2002) · Natural Computing · doi:10.1023/a:1016568309421 · Cited by 1,405 · see citing works
Defining a Standard for Particle Swarm Optimization
Bratton, D. J., & Kennedy, J. (2007) · IEEE Swarm Intelligence Symposium · doi:10.1109/sis.2007.368035 · Cited by 1,356 · see citing works
Particle swarm optimization with particles having quantum behavior
Sun, J., Feng, B., & Xu, W. (2004) · IEEE Congress on Evolutionary Computation (CEC) · doi:10.1109/cec.2004.1330875 · Cited by 1,315 · see citing works
Evolutionary optimization versus particle swarm optimization: Philosophy and performance differences
Angeline, P. J. (1998) · Lecture notes in computer science · doi:10.1007/bfb0040811 · Cited by 1,125 · see citing works
Small worlds and mega-minds: effects of neighborhood topology on particle swarm performance
Kennedy, J. (2003) · IEEE Congress on Evolutionary Computation (CEC) · doi:10.1109/cec.1999.785509 · Cited by 1,061 · see citing works
Using selection to improve particle swarm optimization
Angeline, P. J. (2002) · doi:10.1109/icec.1998.699327 · Cited by 872 · see citing works
A novel particle swarm optimization algorithm with adaptive inertia weight
Nickabadi, A., Ebadzadeh, M. M., & Safabakhsh, R. (2011) · Applied Soft Computing · doi:10.1016/j.asoc.2011.01.037 · Cited by 811 · see citing works
Improving PSO-Based Multi-objective Optimization Using Crowding, Mutation and ∈-Dominance
Sierra, M. R., & Coello, C. A. C. (2005) · Lecture notes in computer science · doi:10.1007/978-3-540-31880-4_35 · Cited by 784 · see citing works
Orthogonal Learning Particle Swarm Optimization
Zhan, Z., Zhang, J., Li, Y., & Shi, Y. (2010) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2010.2052054 · Cited by 734 · see citing works
Bare bones particle swarms
Kennedy, J. (2004) · IEEE Swarm Intelligence Symposium · doi:10.1109/sis.2003.1202251 · Cited by 696 · see citing works
Nonlinear inertia weight variation for dynamic adaptation in particle swarm optimization
Chatterjee, A., & Siarry, P. (2004) · Computers & Operations Research · doi:10.1016/j.cor.2004.08.012 · Cited by 695 · see citing works
On the Computation of All Global Minimizers Through Particle Swarm Optimization
Parsopoulos, K. E., & Vrahatis, M. N. (2004) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2004.826076 · Cited by 682 · see citing works
Strategies for finding good local guides in multi-objective particle swarm optimization (MOPSO)
Mostaghim, S., & Teich, J. (2004) · IEEE Swarm Intelligence Symposium · doi:10.1109/sis.2003.1202243 · Cited by 654 · see citing works
Particle Swarm Optimization With an Aging Leader and Challengers
Chen, W., Zhang, J., Lin, Y., et al. (2012) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2011.2173577 · Cited by 637 · see citing works
An Improved Particle Swarm Optimization for Nonconvex Economic Dispatch Problems
Park, J., Jeong, Y.-W., Shin, J.-R., et al. (2009) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2009.2030293 · Cited by 629 · see citing works
The particle swarm optimization algorithm in size and shape optimization
Fourie, P. C., & Groenwold, A. A. (2002) · Structural and Multidisciplinary Optimization · doi:10.1007/s00158-002-0188-0 · Cited by 493 · see citing works
Dynamic multi-swarm particle swarm optimizer
Liang, J., & Suganthan, P. N. (2005) · IEEE Swarm Intelligence Symposium · doi:10.1109/sis.2005.1501611 · Cited by 487 · see citing works
Self-Organizing Hierarchical Particle Swarm Optimization for Nonconvex Economic Dispatch
Chaturvedi, K. T., Pandit, M., & Srivastava, L. (2008) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2008.926455 · Cited by 486 · see citing works
Enhancing particle swarm optimization using generalized opposition-based learning
Wang, H., Wu, Z., Rahnamayan, S., et al. (2011) · Information Sciences · doi:10.1016/j.ins.2011.03.016 · Cited by 480 · see citing works
Fitness-distance-ratio based particle swarm optimization
Peram, T., Veeramachaneni, K. K., & Mohan, C. K. (2004) · IEEE Swarm Intelligence Symposium · doi:10.1109/sis.2003.1202264 · Cited by 475 · see citing works
Niching Without Niching Parameters: Particle Swarm Optimization Using a Ring Topology
Li, X. (2009) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2009.2026270 · Cited by 467 · see citing works
Discrete Particle Swarm Optimization, illustrated by the Traveling Salesman Problem
Clerc, M. (2004) · Studies in fuzziness and soft computing · doi:10.1007/978-3-540-39930-8_8 · Cited by 465 · see citing works
Hybrid Particle Swarm Optimiser with breeding and subpopulations
Løvbjerg, M., Rasmussen, T., & Krink, T. (2001) · Cited by 429 · see citing works
Diversity enhanced particle swarm optimization with neighborhood search
Wang, H., Sun, H., Li, C., et al. (2012) · Information Sciences · doi:10.1016/j.ins.2012.10.012 · Cited by 408 · see citing works
A Self-Learning Particle Swarm Optimizer for Global Optimization Problems
Li, C., Yang, S., & Nguyễn, T. T. (2011) · IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) · doi:10.1109/tsmcb.2011.2171946 · Cited by 387 · see citing works
Stability analysis of the particle dynamics in particle swarm optimizer
Kadirkamanathan, V., Selvarajah, K., & Fleming, P. J. (2006) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2005.857077 · Cited by 375 · see citing works
A particle swarm optimizer with passive congregation
He, S., Wu, Q., Wen, J., Saunders, J. R., & Paton, R. C. (2004) · Biosystems · doi:10.1016/j.biosystems.2004.08.003 · Cited by 375 · see citing works
Particle swarm, genetic algorithm, and their hybrids: optimization of a profiled corrugated horn antenna
Robinson, J. T., Sinton, S., & Rahmat–Samii, Y. (2003) · Digest - IEEE Antennas and Propagation Society. International Symposium · doi:10.1109/aps.2002.1016311 · Cited by 374 · see citing works
A Study of Global Optimization Using Particle Swarms
Schutte, J. F., & Groenwold, A. A. (2005) · Journal of Global Optimization · doi:10.1007/s10898-003-6454-x · Cited by 368 · see citing works
Stereotyping: improving particle swarm performance with cluster analysis
Kennedy, J. (2002) · IEEE Congress on Evolutionary Computation (CEC) · doi:10.1109/cec.2000.870832 · Cited by 354 · see citing works
Particle swarm and ant colony algorithms hybridized for improved continuous optimization
Shelokar, P., Siarry, P., Jayaraman, V., et al. (2006) · Applied Mathematics and Computation · doi:10.1016/j.amc.2006.09.098 · Cited by 346 · see citing works
A modified particle swarm optimizer with dynamic adaptation
Yang, X., Yuan, J., Yuan, J., & Mao, H. (2006) · Applied Mathematics and Computation · doi:10.1016/j.amc.2006.12.045 · Cited by 340 · see citing works
Adaptive particle swarm optimization: detection and response to dynamic systems
Hu, X., & Eberhart, R. C. (2003) · IEEE Congress on Evolutionary Computation (CEC) · doi:10.1109/cec.2002.1004492 · Cited by 339 · see citing works
Combined heat and power economic dispatch problem solution using particle swarm optimization with time varying acceleration coefficients
Mohammadi‐Ivatloo, B., Moradi-Dalvand, M., & Rabiee, A. (2012) · Electric Power Systems Research · doi:10.1016/j.epsr.2012.08.005 · Cited by 334 · see citing works
A new locally convergent particle swarm optimiser
van den Bergh, F., & Engelbrecht, A. P. (2003) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/icsmc.2002.1176018 · Cited by 320 · see citing works
The behavior of particles
Kennedy, J. (1998) · Lecture notes in computer science · doi:10.1007/bfb0040809 · Cited by 320 · see citing works
A novel multi-objective particle swarm optimization with multiple search strategies
Lin, Q., Li, J., Du, Z., et al. (2015) · European Journal of Operational Research · doi:10.1016/j.ejor.2015.06.071 · Cited by 306 · see citing works
Use of intelligent-particle swarm optimization in electromagnetics
Ciuprina, G., Ioan, D., & Munteanu, I. (2002) · IEEE Transactions on Magnetics · doi:10.1109/20.996266 · Cited by 297 · see citing works
A hybrid particle swarm optimization and genetic algorithm for closed-loop supply chain network design in large-scale networks
Soleimani, H., & Govindan, K. (2014) · Applied Mathematical Modelling · doi:10.1016/j.apm.2014.12.016 · Cited by 292 · see citing works
Dissipative particle swarm optimization
Xie, X., Zhang, W.-J., & Yang, Z.-L. (2003) · IEEE Congress on Evolutionary Computation (CEC) · doi:10.1109/cec.2002.1004457 · Cited by 271 · see citing works
Economic Load Dispatch—A Comparative Study on Heuristic Optimization Techniques With an Improved Coordinated Aggregation-Based PSO
Vlachogiannis, J. G., & Lee, K. Y. (2009) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2009.2016524 · Cited by 265 · see citing works
Particle swarm optimization with mutation
Stacey, A., Jancic, M., & Grundy, I. H. (2004) · doi:10.1109/cec.2003.1299838 · Cited by 252 · see citing works
Solving economic load dispatch problems in power systems using chaotic and Gaussian particle swarm optimization approaches
Coelho, L. D. S., & Lee, C.-S. (2007) · International Journal of Electrical Power & Energy Systems · doi:10.1016/j.ijepes.2007.08.001 · Cited by 251 · see citing works
Multimodal function optimization based on particle swarm optimization
Seo, J.-H., Im, C., Heo, C.-G., et al. (2006) · IEEE Transactions on Magnetics · doi:10.1109/tmag.2006.871568 · Cited by 207 · see citing works
A hybrid method of chaotic particle swarm optimization and linear interior for reactive power optimisation
Chuanwen, J., & Bompard, E. F. (2004) · Mathematics and Computers in Simulation · doi:10.1016/j.matcom.2004.10.003 · Cited by 191 · see citing works
Mean and Variance of the Sampling Distribution of Particle Swarm Optimizers During Stagnation
Poli, R. (2009) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2008.2011744 · Cited by 190 · see citing works
Modified binary particle swarm optimization
Lee, S., Soak, S.-M., Oh, S., et al. (2008) · Progress in Natural Science Materials International · doi:10.1016/j.pnsc.2008.03.018 · Cited by 189 · see citing works
Competitive and cooperative particle swarm optimization with information sharing mechanism for global optimization problems
Li, Y., Zhan, Z., Lin, S., et al. (2014) · Information Sciences · doi:10.1016/j.ins.2014.09.030 · Cited by 188 · see citing works
Extending particle swarm optimisers with self-organized criticality
Løvbjerg, M., & Krink, T. (2003) · IEEE Congress on Evolutionary Computation (CEC) · doi:10.1109/cec.2002.1004479 · Cited by 178 · see citing works
Stochastic Stability Analysis of the Linear Continuous and Discrete PSO Models
Fernández‐Martínez, J. L., & García–Gonzalo, E. (2010) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2010.2053935 · Cited by 167 · see citing works
PS–ABC: A hybrid algorithm based on particle swarm and artificial bee colony for high-dimensional optimization problems
Li, Z., Li, Z., Wang, W., et al. (2015) · Expert Systems with Applications · doi:10.1016/j.eswa.2015.07.043 · Cited by 163 · see citing works
A hybrid boundary condition for robust particle swarm optimization
Huang, T., & Mohan, A. S. (2005) · IEEE Antennas and Wireless Propagation Letters · doi:10.1109/lawp.2005.846166 · Cited by 154 · see citing works
A new particle swarm optimization algorithm with adaptive inertia weight based on Bayesian techniques
Zhang, L., Tang, Y., Hua, C., & Guan, X. (2014) · Applied Soft Computing · doi:10.1016/j.asoc.2014.11.018 · Cited by 153 · see citing works
Don't push me! Collision-avoiding swarms
Blackwell, T., & Bentley, P. J. (2003) · IEEE Congress on Evolutionary Computation (CEC) · doi:10.1109/cec.2002.1004497 · Cited by 146 · see citing works
A Hamming distance based binary particle swarm optimization (HDBPSO) algorithm for high dimensional feature selection, classification and validation
Banka, H., & Dara, S. (2014) · Pattern Recognition Letters · doi:10.1016/j.patrec.2014.10.007 · Cited by 146 · see citing works
Optimization using civilized swarm: Solution to economic dispatch with multiple minima
Selvakumar, A. I., & Thanushkodi, K. (2008) · Electric Power Systems Research · doi:10.1016/j.epsr.2008.05.001 · Cited by 132 · see citing works
Combining Particle Swarm Optimisation with angle modulation to solve binary problems
Pamparà, G., Franken, N., & Engelbrecht, A. P. (2005) · IEEE Congress on Evolutionary Computation (CEC) · doi:10.1109/cec.2005.1554671 · Cited by 131 · see citing works
A hybrid particle swarm optimization algorithm for high-dimensional problems
Jia, D., Zheng, G., Qu, B., et al. (2011) · Computers & Industrial Engineering · doi:10.1016/j.cie.2011.06.024 · Cited by 126 · see citing works
A Novel Binary Particle Swarm Optimization Method Using Artificial Immune System
Afshinmanesh, F., Marandi, A., & Rahimi‐Kian, A. (2005) · IEEE EUROCON - International Conference on Computer as a Tool (EUROCON) · doi:10.1109/eurcon.2005.1629899 · Cited by 114 · see citing works
Better Spread and Convergence: Particle Swarm Multiobjective Optimization Using the Maximin Fitness Function
Li, X. (2004) · Lecture notes in computer science · doi:10.1007/978-3-540-24854-5_11 · Cited by 112 · see citing works
A New Particle Swarm Optimization Technique
Yang, C., & Simon, D. (2006) · International Conference on Systems Engineering · doi:10.1109/icseng.2005.9 · Cited by 112 · see citing works
A modification to particle swarm optimization algorithm
Fan, H. (2002) · Engineering Computations · doi:10.1108/02644400210450378 · Cited by 111 · see citing works
Adaptive particle swarm optimization
Yasuda, K., Ide, A., & Iwasaki, N. (2004) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/icsmc.2003.1244633 · Cited by 111 · see citing works
Low-discrepancy sequence initialized particle swarm optimization algorithm with high-order nonlinear time-varying inertia weight
Yang, C., Gao, W., Liu, N., et al. (2015) · Applied Soft Computing · doi:10.1016/j.asoc.2015.01.004 · Cited by 109 · see citing works
A novel crazy swarm optimized economic load dispatch for various types of cost functions
Roy, R., & Ghoshal, S. P. (2007) · International Journal of Electrical Power & Energy Systems · doi:10.1016/j.ijepes.2007.07.007 · Cited by 106 · see citing works
Economic environmental dispatch using an enhanced multi-objective cultural algorithm
Zhang, R., Zhou, J., Li, M., et al. (2013) · Electric Power Systems Research · doi:10.1016/j.epsr.2013.01.010 · Cited by 104 · see citing works
Adaptively choosing niching parameters in a PSO
Bird, S., & Li, X. (2006) · Genetic and Evolutionary Computation Conference (GECCO) · doi:10.1145/1143997.1143999 · Cited by 103 · see citing works
Dynamic mentoring and self-regulation based particle swarm optimization algorithm for solving complex real-world optimization problems
Tanweer, M. R., Sundaram, S., & Sundararajan, N. (2015) · Information Sciences · doi:10.1016/j.ins.2015.07.035 · Cited by 102 · see citing works
The LifeCycle Model: Combining Particle Swarm Optimisation, Genetic Algorithms and HillClimbers
Krink, T., & Løvbjerg, M. (2002) · Lecture notes in computer science · doi:10.1007/3-540-45712-7_60 · Cited by 102 · see citing works
Adaptive fuzzy particle swarm optimization for global optimization of multimodal functions
Juang, Y., Tung, S.-L., & Chiu, H.-C. (2010) · Information Sciences · doi:10.1016/j.ins.2010.11.025 · Cited by 102 · see citing works
Solving systems of unconstrained equations using particle swarm optimization
Brits, R., Engelbrecht, A. P., & van den Bergh, F. (2003) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/icsmc.2002.1176019 · Cited by 98 · see citing works
Neighborhood topologies in fully-informed and best-of-neighborhood particle swarms
Kennedy, J., & Mendes, R. (2003) · IEEE Conference on Soft Computing in Industrial Applications (SMCia) · doi:10.1109/smcia.2003.1231342 · Cited by 98 · see citing works
A cooperative particle swarm optimizer with stochastic movements for computationally expensive numerical optimization problems
Ngo, T. T., Sadollah, A., & Kim, J. H. (2016) · Journal of Computational Science · doi:10.1016/j.jocs.2016.01.004 · Cited by 96 · see citing works
Initializing the Particle Swarm Optimizer Using the Nonlinear Simplex Method
Parsopoulos, K. E. (2002) · Cited by 95 · see citing works
Choosing a starting configuration for particle swarm optimization
(2004) · IEEE International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2004.1380986 · Cited by 95 · see citing works
Feedback learning particle swarm optimization
Tang, Y. S., Wang, Z., & Fang, J. (2011) · Applied Soft Computing · doi:10.1016/j.asoc.2011.07.012 · Cited by 94 · see citing works
A particle swarm optimization method with enhanced global search ability for design optimizations of electromagnetic devices
Ho, S. L., Yang, S., Ni, G., et al. (2006) · IEEE Transactions on Magnetics · doi:10.1109/tmag.2006.871426 · Cited by 91 · see citing works
The Lévy Particle Swarm
Richer, T., & Blackwell, T. (2006) · doi:10.1109/cec.2006.1688394 · Cited by 90 · see citing works
Particle swarms and population diversity
Blackwell, T. (2005) · Soft Computing · doi:10.1007/s00500-004-0420-5 · Cited by 90 · see citing works
Tuning PSO Parameters Through Sensitivity Analysis
Bartz–Beielstein, T., Parsopoulos, K. E., & Vrahatis, M. N. (2002) · doi:10.17877/de290r-15305 · Cited by 88 · see citing works
Adaptive Inertia Weight Particle Swarm Optimization
Qin, Z., Yu, F., Shi, Z., et al. (2006) · Lecture notes in computer science · doi:10.1007/11785231_48 · Cited by 87 · see citing works
Adaptive acceleration coefficients for a new search diversification strategy in particle swarm optimization algorithms
Ardizzon, G., Cavazzini, G., & Pavesi, G. (2014) · Information Sciences · doi:10.1016/j.ins.2014.12.024 · Cited by 85 · see citing works
Accelerating particle swarm optimization using crisscross search
Meng, A., Li, Z., Yin, H., et al. (2015) · Information Sciences · doi:10.1016/j.ins.2015.08.018 · Cited by 84 · see citing works
Generalized radial basis function neural network based on an improved dynamic particle swarm optimization and AdaBoost algorithm
Lu, J., Hu, H., & Bai, Y. (2014) · Neurocomputing · doi:10.1016/j.neucom.2014.10.065 · Cited by 82 · see citing works
A decentralized quantum-inspired particle swarm optimization algorithm with cellular structured population
Fang, W., Sun, J. J., Chen, H., et al. (2015) · Information Sciences · doi:10.1016/j.ins.2015.09.055 · Cited by 82 · see citing works
A New Approach to Improve Particle Swarm Optimization
Zhang, L., Yu, H., & Hu, S. (2003) · Lecture notes in computer science · doi:10.1007/3-540-45105-6_12 · Cited by 79 · see citing works
Dynamic search space squeezing strategy based intelligent algorithm solutions to economic dispatch with multiple fuels
Barisal, A. K. (2012) · International Journal of Electrical Power & Energy Systems · doi:10.1016/j.ijepes.2012.08.049 · Cited by 79 · see citing works
Port throughput forecasting by MARS-RSVR with chaotic simulated annealing particle swarm optimization algorithm
Geng, J., Li, M., Dong, Z., & Liao, Y. (2014) · Neurocomputing · doi:10.1016/j.neucom.2014.06.070 · Cited by 78 · see citing works
Hybrid: Particle Swarm Optimization–Genetic Algorithm and Particle Swarm Optimization–Shuffled Frog Leaping Algorithm for long-term generator maintenance scheduling
Samuel, G. G., & Rajan, C. C. A. (2014) · International Journal of Electrical Power & Energy Systems · doi:10.1016/j.ijepes.2014.10.042 · Cited by 77 · see citing works
Comparing particle swarms for tracking extrema in dynamic environments
Li, X., & Dam, H. K. (2004) · doi:10.1109/cec.2003.1299887 · Cited by 77 · see citing works
Neighborhood Re-structuring in Particle Swarm Optimization
Mohais, A. S., Mendes, R., Ward, C., et al. (2005) · Lecture notes in computer science · doi:10.1007/11589990_80 · Cited by 74 · see citing works
Fuzzy PSO: a generalization of particle swarm optimization
Abdelbar, A. M., Abdelshahid, S., & Wunsch, D. C. (2006) · IEEE International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2005.1556004 · Cited by 73 · see citing works
A modified particle swarm optimization with multiple subpopulations for multimodal function optimization problems
Chang, W. (2015) · Applied Soft Computing · doi:10.1016/j.asoc.2015.04.002 · Cited by 72 · see citing works
Optimal multiple distributed generation output through rank evolutionary particle swarm optimization
Jamian, J. J., Mustafa, M. W., & Mokhlis, H. (2014) · Neurocomputing · doi:10.1016/j.neucom.2014.11.001 · Cited by 71 · see citing works
Stagnation Analysis in Particle Swarm Optimisation or What Happens When Nothing Happens
Clerc, M., & Poli, E. R. (2006) · Cited by 70 · see citing works
The Kalman Swarm: A New Approach to Particle Motion in Swarm Optimization.
Monson, C. K., & Seppi, K. D. (2004) · Cited by 68 · see citing works
Probability and dynamics in the particle swarm
Kennedy, J. (2004) · Congress on Evolutionary Computation · doi:10.1109/cec.2004.1330877 · Cited by 68 · see citing works
Multi-population Cooperative Particle Swarm Optimization
Niu, B., Zhu, Y., & He, X. (2005) · Lecture notes in computer science · doi:10.1007/11553090_88 · Cited by 67 · see citing works
Tribe-PSO: A novel global optimization algorithm and its application in molecular docking
Chen, K., Li, T., & Cao, T. (2005) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/j.chemolab.2005.06.017 · Cited by 65 · see citing works
Simulation of a new hybrid particle swarm optimization algorithm
Noel, M. M., & Jannett, T. C. (2004) · doi:10.1109/ssst.2004.1295638 · Cited by 65 · see citing works
Non-parametric particle swarm optimization for global optimization
Beheshti, Z., & Shamsuddin, S. M. (2014) · Applied Soft Computing · doi:10.1016/j.asoc.2014.12.015 · Cited by 61 · see citing works
Some Insight Over New Variations of the Particle Swarm Optimization Method
Selleri, S., Mussetta, M., Pirinoli, P., et al. (2006) · IEEE Antennas and Wireless Propagation Letters · doi:10.1109/lawp.2006.874071 · Cited by 59 · see citing works
Multi-phase generalization of the particle swarm optimization algorithm
Al-kazemi, B., & Mohan, C. K. (2003) · IEEE Congress on Evolutionary Computation (CEC) · doi:10.1109/cec.2002.1006283 · Cited by 57 · see citing works
Continuous swarm optimization technique with stability analysis
Emara, H. M., & Fattah, H. A. A. (2004) · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference · doi:10.23919/acc.2004.1383892 · Cited by 57 · see citing works
Particle Swarm Optimization inspired by starling flock behavior
Netjinda, N., Achalakul, T., & Sirinaovakul, B. (2015) · Applied Soft Computing · doi:10.1016/j.asoc.2015.06.052 · Cited by 56 · see citing works
A Hybrid Particle Swarm Optimization (PSO)‐Simplex Algorithm for Damage Identification of Delaminated Beams
Qian, X., Cao, M., Su, Z., & Chen, J. (2012) · Mathematical Problems in Engineering · doi:10.1155/2012/607418 · Cited by 55 · see citing works
A new quantum-behaved particle swarm optimization based on cultural evolution mechanism for multiobjective problems
Liu, T., Jiao, L., Ma, W., et al. (2016) · Knowledge-Based Systems · doi:10.1016/j.knosys.2016.03.009 · Cited by 53 · see citing works
Adaptive particle swarmi optimization using velocity information of swarm
Yasuda, K., & Iwasaki, N. (2005) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/icsmc.2004.1400880 · Cited by 52 · see citing works
Improved particle swarm optimization technique using hard boundary conditions
Mikki, S. M., & Kishk, A. A. (2005) · Microwave and Optical Technology Letters · doi:10.1002/mop.21004 · Cited by 51 · see citing works
Arbitrary function optimisation with metaheuristics
García‐Martínez, C., Rodríguez, F. J., & Lozano, M. (2012) · Soft Computing · doi:10.1007/s00500-012-0881-x · Cited by 49 · see citing works
PPSO: PCA based particle swarm optimization for solving conditional nonlinear optimal perturbation
Mu, B., Wen, S., Yuan, S., et al. (2015) · Computers & Geosciences · doi:10.1016/j.cageo.2015.06.016 · Cited by 48 · see citing works
Particle swarm optimization with adaptive time-varying topology connectivity
Lim, W. H., & Isa, N. A. M. (2014) · Applied Soft Computing · doi:10.1016/j.asoc.2014.08.013 · Cited by 48 · see citing works
Scalability of niche PSO
Brits, R., Engelbrecht, A. P., & van den Bergh, F. (2004) · IEEE Swarm Intelligence Symposium · doi:10.1109/sis.2003.1202273 · Cited by 45 · see citing works
Solving a new multi-objective multi-route flexible flow line problem by multi-objective particle swarm optimization and NSGA-II
Ghodratnama, A., Jolai, F., & Tavakkoli-Moghaddam, R. R. (2014) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2014.06.009 · Cited by 45 · see citing works
A hybrid Wavelet Neural Network and Switching Particle Swarm Optimization algorithm for face direction recognition
Lü, Y., Zeng, N., Liu, Y., et al. (2015) · Neurocomputing · doi:10.1016/j.neucom.2014.12.026 · Cited by 45 · see citing works
Particle Swarm for the Traveling Salesman Problem
Goldbarg, E. F. G., de Souza, G. R., & Goldbarg, M. C. (2006) · Lecture notes in computer science · doi:10.1007/11730095_9 · Cited by 44 · see citing works
Hybrid particle swarm optimization with mutation for optimizing industrial product lines: An application to a mixed solution space considering both discrete and continuous design variables
Tsafarakis, S., Saridakis, C., Baltas, G., & Matsatsinis, N. F. (2013) · Industrial Marketing Management · doi:10.1016/j.indmarman.2013.03.002 · Cited by 43 · see citing works
Dynamics and Stability of the Sampling Distribution ofParticle Swarm Optimisers via Moment Analysis
Poli, R. (2008) · Journal of Artificial Evolution and Applications · doi:10.1155/2008/761459 · Cited by 42 · see citing works
A mechanism based on Artificial Bee Colony to generate diversity in Particle Swarm Optimization
Vitorino, L. N., Ribeiro, S. F., & Bastos-Filho, C. J. A. (2014) · Neurocomputing · doi:10.1016/j.neucom.2013.03.076 · Cited by 42 · see citing works
The Kalman Swarm
Monson, C. K., & Seppi, K. D. (2004) · Lecture notes in computer science · doi:10.1007/978-3-540-24854-5_13 · Cited by 41 · see citing works
Convergence and stochastic stability analysis of particle swarm optimization variants with generic parameter distributions
García–Gonzalo, E., & Fernández‐Martínez, J. L. (2014) · Applied Mathematics and Computation · doi:10.1016/j.amc.2014.10.066 · Cited by 41 · see citing works
A novel hybrid adaptive collaborative approach based on particle swarm optimization and local search for dynamic optimization problems
Sharifi, A., Kordestani, J. K., Mahdaviani, M., et al. (2015) · Applied Soft Computing · doi:10.1016/j.asoc.2015.04.001 · Cited by 39 · see citing works
Design optimization of PM couplings using hybrid Particle Swarm Optimization-Simplex Method (PSO-SM) Algorithm
El-Wakeel, A. S. (2014) · Electric Power Systems Research · doi:10.1016/j.epsr.2014.05.003 · Cited by 36 · see citing works
Unequal Clustering by Improved Particle Swarm Optimization in Wireless Sensor Network
Salehian, S., & Subraminiam, S. K. (2015) · Procedia Computer Science · doi:10.1016/j.procs.2015.08.433 · Cited by 34 · see citing works
A Parallel Vector-Based Particle Swarm Optimizer
Schoeman, I., & Engelbrecht, A. P. (2005) · Springer eBooks · doi:10.1007/3-211-27389-1_64 · Cited by 34 · see citing works
Niching ability of basic particle swarm optimization algorithms
Engelbrecht, A. P., Masiye, B. S., & Pamparà, G. (2005) · IEEE Swarm Intelligence Symposium · doi:10.1109/sis.2005.1501650 · Cited by 33 · see citing works
Entropy based Binary Particle Swarm Optimization and classification for ear detection
Ganesh, M. R., Krishna, R., Manikantan, K., et al. (2013) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2013.07.022 · Cited by 32 · see citing works
Search performance improvement of Particle Swarm Optimization by second best particle information
Shin, Y.-B., & Kita, E. (2014) · Applied Mathematics and Computation · doi:10.1016/j.amc.2014.08.013 · Cited by 32 · see citing works
Preserving Diversity in Particle Swarm Optimisation
Hendtlass, T. (2007) · Springer eBooks · doi:10.1007/3-540-45034-3_4 · Cited by 31 · see citing works
Adaptive division of labor particle swarm optimization
Lim, W. H., & Isa, N. A. M. (2015) · Expert Systems with Applications · doi:10.1016/j.eswa.2015.03.025 · Cited by 31 · see citing works
Evolving the Structure of the Particle Swarm Optimization Algorithms
Dioşan, L. S., & Oltean, M. (2006) · Lecture notes in computer science · doi:10.1007/11730095_3 · Cited by 30 · see citing works
Lockage scheduling of Three Gorges-Gezhouba dams by hybrid of chaotic particle swarm optimization and heuristic-adjusted strategies
Yuan, Y., Ji, B., Yuan, X., et al. (2015) · Applied Mathematics and Computation · doi:10.1016/j.amc.2015.08.009 · Cited by 29 · see citing works
A new approach to particle swarm optimization algorithm
Gościniak, I. (2014) · Expert Systems with Applications · doi:10.1016/j.eswa.2014.07.034 · Cited by 29 · see citing works
Why does it need velocity?
Kennedy, J. (2005) · IEEE Swarm Intelligence Symposium · doi:10.1109/sis.2005.1501600 · Cited by 29 · see citing works
A new sense-through-foliage target recognition method based on hybrid differential evolution and self-adaptive particle swarm optimization-based support vector machine
Zhai, S., & Jiang, T. (2014) · Neurocomputing · doi:10.1016/j.neucom.2014.08.017 · Cited by 28 · see citing works
Minds and Cultures: Particle Swarm Implications
Kennedy, J. (1997) · Cited by 27 · see citing works
A hybrid algorithm based on particle swarm and chemical reaction optimization for multi-object problems
Li, Z., Nguyen, T. T., Chen, S., et al. (2015) · Applied Soft Computing · doi:10.1016/j.asoc.2015.06.036 · Cited by 27 · see citing works
A chaotic particle swarm optimization exploiting a virtual quartic objective function based on the personal and global best solutions
Tatsumi, K., Ibuki, T., & Tanino, T. (2013) · Applied Mathematics and Computation · doi:10.1016/j.amc.2013.03.029 · Cited by 27 · see citing works
A basic study of adaptive particle swarm optimization
Ide, A., & Yasuda, K. (2005) · Electrical Engineering in Japan · doi:10.1002/eej.20077 · Cited by 26 · see citing works
A new class of operators to accelerate particle swarm optimization
Ting, T.-O., Rao, M. V. C., Lon, C. K., et al. (2004) · doi:10.1109/cec.2003.1299389 · Cited by 26 · see citing works
Bayesian optimization models for particle swarms
Monson, C. K., & Seppi, K. D. (2005) · Genetic and Evolutionary Computation Conference (GECCO) · doi:10.1145/1068009.1068039 · Cited by 25 · see citing works
Application of Particle Swarm Optimization for Optimizing the Process Parameters in Turning of PEEK CF30 Composites
Hanafi, I., Cabrera, F. M., Dimane, F., et al. (2016) · Procedia Technology · doi:10.1016/j.protcy.2016.01.044 · Cited by 23 · see citing works
Modeling of a solid oxide fuel cell power plant using an ensemble of neural networks based on a combination of the adaptive particle swarm optimization and Levenberg–Marquardt algorithms
Shirkhani, R., Jazayeri‐Rad, H., & Hashemi, S. J. (2014) · Journal of Natural Gas Science and Engineering · doi:10.1016/j.jngse.2014.07.004 · Cited by 22 · see citing works
Optimizing semiconductor devices by self-organizing particle swarm
Xie, X., Zhang, W.-J., & Bi, D.-C. (2005) · Congress on Evolutionary Computation · doi:10.1109/cec.2004.1331144 · Cited by 22 · see citing works
Bare Bones Particle Swarms with Jumps
al‐Rifaie, M. M., & Blackwell, T. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-32650-9_5 · Cited by 20 · see citing works
Self-adaptive particle swarm optimization with multiple velocity strategies and its application for p-Xylene oxidation reaction process optimization
Fan, Q., & Yan, X. (2014) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/j.chemolab.2014.09.002 · Cited by 19 · see citing works
Compensatory neural fuzzy network with symbiotic particle swarm optimization for temperature control
Peng, C., & Chen, C.-H. (2014) · Applied Mathematical Modelling · doi:10.1016/j.apm.2014.05.040 · Cited by 19 · see citing works
Improving the performance of particle swarm optimization using adaptive critics designs
Doctor, S., & Venayagamoorthy, G. K. (2005) · IEEE Swarm Intelligence Symposium · doi:10.1109/sis.2005.1501649 · Cited by 18 · see citing works
Acceleration factor harmonious particle swarm optimizer
Chen, J., Pan, F., & Cai, T. (2006) · Machine Intelligence Research · doi:10.1007/s11633-006-0041-9 · Cited by 17 · see citing works
Research on particle swarm optimization and its application
Chun-tao, G. (2010) · Journal of Harbin University of Commerce · Cited by 17 · see citing works
Adaptive Particle Swarm Optimization with Feedback Control of Diversity
Jie, J., Zeng, J., & Han, C. (2006) · Lecture notes in computer science · doi:10.1007/11816102_9 · Cited by 16 · see citing works
Repel the swarm to the optimum!
Leontitsis, A., Kontogiorgos, D., & Pagge, J. (2005) · Applied Mathematics and Computation · doi:10.1016/j.amc.2005.04.004 · Cited by 16 · see citing works
Enhanced Particle Swarm Optimization Through External Memory Support
Acan, A., & Günay, A. C. (2005) · IEEE Congress on Evolutionary Computation (CEC) · doi:10.1109/cec.2005.1554916 · Cited by 15 · see citing works
Particle swarm optimization with stochastic selection of perturbation-based chaotic updating system
Tatsumi, K., Ibuki, T., & Tanino, T. (2015) · Applied Mathematics and Computation · doi:10.1016/j.amc.2015.07.098 · Cited by 14 · see citing works
A parallel system for adaptive optics based on parallel mutation PSO algorithm
Chen, Y., Feng, Y., & Li, X. (2013) · Optik · doi:10.1016/j.ijleo.2013.06.042 · Cited by 13 · see citing works
An improved particle swarm optimization algorithm with neighborhoods topologies
Jian, W., Xue, Y., & Qian, J. (2005) · doi:10.1109/icmlc.2004.1382189 · Cited by 13 · see citing works
Estimation of Model Parameters Using Composite Particle Swarm Optimization
Hu, S. (2005) · Journal of Chemical Engineering of Chinese Universities · Cited by 12 · see citing works
A Differential Evolutionary Particle Swarm Optimization with Controller
Zeng, J., Cui, Z., & Wang, L. (2005) · Lecture notes in computer science · doi:10.1007/11539902_57 · Cited by 11 · see citing works
MIMO radar array synthesis using QPSO with normal distributed contraction-expansion factor
Liu, H., Yang, G., & Song, G. (2011) · Procedia Engineering · doi:10.1016/j.proeng.2011.08.460 · Cited by 11 · see citing works
Acceleration Factor Harmonious Particle Swarm Optimizer
Jie, J., Chen, Feng, et al. (2006) · 国际自动化与计算杂志 · Cited by 11 · see citing works
Designing particle swarm optimization with regression trees
Bartz–Beielstein, T., Parsopoulos, K. E., de Vegt, M., et al. (2004) · Technische Universität Dortmund Eldorado (Technische Universität Dortmund) · doi:10.17877/de290r-5432 · Cited by 10 · see citing works
Particle swarm optimization with area of influence: increasing the effectiveness of the swarm
Binkley, K. J., & Hagiwara, M. (2005) · IEEE Swarm Intelligence Symposium · doi:10.1109/sis.2005.1501601 · Cited by 10 · see citing works
Using relaxation velocity update strategy to improve particle swarm optimization
Liu, Y., Qin, Z., Xu, Z., et al. (2005) · doi:10.1109/icmlc.2004.1382218 · Cited by 10 · see citing works
Process identification using a new component analysis model and particle swarm optimization
Fan, S. S., Lin, Y.-T., Fan, C.-M., et al. (2009) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/j.chemolab.2009.07.006 · Cited by 9 · see citing works
Local Optimum Embranchment Based Convergence Guarantee Particle Swarm Optimization and Its Application in Transmission Network Planning
Jin, Y.-X., Cheng, H., Yan, J.-Y., et al. (2005) · doi:10.1109/tdc.2005.1546847 · Cited by 7 · see citing works
Swarm Double-Tabu Search
Wen, W., & Liu, G. (2005) · Lecture notes in computer science · doi:10.1007/11539902_156 · Cited by 5 · see citing works
An adaptive inertia weight strategy for particle swarm optimizer
Lei, K., Wang, F., Qiu, Y., et al. (2005) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.664515 · Cited by 5 · see citing works
An improved particle swarm optimization and its application in long-term streamflow forecast
Liu, F., Zhou, J., Fang, R.-C., et al. (2005) · International Conference on Machine Learning and Cybernetics · doi:10.1109/icmlc.2005.1527440 · Cited by 5 · see citing works
Scheduling Optimization of Mixed Model Assembly Lines with Hybrid Particle Swarm Optimization Algorithm
Bin-sen, C. (2006) · Industrial Engineering and Management · Cited by 4 · see citing works

Flagged first, then by citations

Sorted by citations

Particle Swarm Optimization: A Comprehensive Survey
Shami, T. M., El-Saleh, A. A., Alswaitti, M., Al-Tashi, Q., Summakieh, M. A., & Mirjalili, S. (2022) · IEEE Access · doi:10.1109/access.2022.3142859 · Cited by 1,433 · see citing works
Router: fog enabled cloud based intelligent resource management approach for smart home iot devices
Gill, S. S., Garraghan, P., & Buyya, R. (2019) · Journal of Systems and Software · doi:10.1016/j.jss.2019.04.058 · Cited by 165 · see citing works
Cybersecurity for Industrial IoT (IIoT): Threats, countermeasures, challenges and future directions
Mekala, S. H., Baig, Z., Anwar, A., & Zeadally, S. (2023) · Computer Communications · doi:10.1016/j.comcom.2023.06.020 · Cited by 111 · see citing works
Review of Ai Applications in Harmonic Analysis in Power Systems
Eslami, A., Negnevitsky, M., Franklin, E., & Lyden, S. (2022) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2021.111897 · Cited by 109 · see citing works
Cyberbullying Sexism Harassment Identification by Metaheurustics-Tuned eXtreme Gradient Boosting
Dobrojevic, M., Jovanovic, L., Babic, L., Cajic, M., Zivkovic, T., Zivkovic, M., Muthusamy, S., Antonijevic, M., & Bacanin, N. (2024) · Computers, Materials & Continua · doi:10.32604/cmc.2024.054459 · Cited by 75 · see citing works
“…other contemporary optimizers, which were tested under the same experimental conditions, with the goal of establishing rigid comparative analysis: COA [11], GA [29], PSO [25], FA [24], Sine cosine algorithm (SCA) [30], Sinh cosh algorithm (SCHA) [31], and Reptile search algorithm (RSA) [32].”
Estimating the State of Health for Lithium-ion Batteries: A Particle Swarm Optimization-Assisted Deep Domain Adaptation Approach
Ma, G., Wang, Z., Liu, W., Fang, J., Zhang, Y., Ding, H., & Yuan, Y. (2023) · IEEE/CAA Journal of Automatica Sinica · doi:10.1109/jas.2023.123531 · Cited by 70 · see citing works

Research on Swarm Size of Multi-swarm Particle Swarm Optimization Algorithm
Shen, Y., Li, Y., Kang, H., et al. (2018) · IEEE International Conference on Computer and Communications (ICCC) · doi:10.1109/compcomm.2018.8781013 · Cited by 31 · see citing works
Hybrid particle swarm optimization and its application
Xiao, D. (2008) · Journal of Chemical Industry and Engineering · Cited by 1 · see citing works
Center Particle Swarm Optimization Algorithm
Xiaojing, Y., Qingju, J., & Xinke, L. (2019) · IEEE Information Technology, Networking, Electronic and Automation Control Conference (ITNEC) · doi:10.1109/itnec.2019.8729510 · Cited by 43 · see citing works
A Random Particle Swarm Optimization Algorithm with Application
Pan, J. H., Wang, H., & Yang, X. G. (2013) · Advanced materials research · doi:10.4028/www.scientific.net/amr.634-638.3940 · Cited by 14 · see citing works
Wiener model identification based on adaptive particle swarm optimization
Hou, Z. (2008) · International Conference on Machine Learning and Cybernetics · doi:10.1109/icmlc.2008.4620558 · Cited by 12 · see citing works

Authors: Wang, D., Tan, D., & Liu, L.
Affiliations: Zhengzhou University (CN)
People's Bank of China (CN)
Corresponding author: Wang, Dongshu
ORCID: Wang, Dongshu
Liu, Lei
Venue: Soft Computing
Publisher: Springer Science and Business Media LLC
Published: 2017-01-17
Volume: 22
Issue: 2
Pages: 387-408
ISSN: 1432-7643 (ISSN-L)
1433-7479
DOI: 10.1007/s00500-016-2474-6
OpenAlex: W2573137292
Cited by: 3,343
References: 194
Citations by year: 2026: 442 · 2025: 862 · 2024: 697 · 2023: 465 · 2022: 349 · 2021: 271 · 2020: 149 · 2019: 51 · 2018: 34 · 2017: 17 · 2016: 5 · 2015: 1
FWCI: 40.94
Type: journal article
Language: en
Open access: closed
Licence: www.springer.com/tdm (unspecified)
Locations: Soft Computing (publishedVersion)
Funders: Natiinal Natural Science Funds of China (61174085)
Topics: Physical Sciences › Computer Science › Artificial Intelligence › Metaheuristic Optimization Algorithms Research
Physical Sciences › Computer Science › Computer Networks and Communications › Distributed Control Multi-Agent Systems
Physical Sciences › Engineering › Aerospace Engineering › Antenna Design and Optimization
Keywords: particle swarm optimization, swarm intelligence, collective behavior, algorithm variants, parameter selection, topological structure, discrete particle swarm optimization, parallel particle swarm optimization, multi-objective optimization, engineering applications

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Particle swarm optimization algorithm: An overview

Integrity signals

Claims the paper makes

Cites

Cited by

Related

Record

About these checks