PSO Bibliography

Theoretical Studies

1
J. Kennedy, R.C. Eberhart, and Y. Shi.
Swarm intelligence.
Morgan Kaufmann Publishers, San Francisco, 2001.

2
K. E. Parsopoulos and M. N. Vrahatis.
Recent approaches to global optimization problems through particle swarm optimization.
Natural Computing: an international journal, 1(2-3):235-306, 2002.

3
Maurice Clerc and James Kennedy.
The particle swarm - explosion, stability, and convergence in a multidimensional complex space.
IEEE Trans. Evolutionary Computation, 6(1):58-73, 2002.

4
Frans van den Bergh.
An analysis of particle swarm optimizers.
PhD thesis, University of Pretoria, South Africa, 2002.

5
Ioan Cristian Trelea.
The particle swarm optimization algorithm: convergence analysis and parameter selection.
Inf. Process. Lett., 85(6):317-325, 2003.

6
Y. Shi and R.C. Eberhart.
Parameter selection in particle swarm optimization.
In Proceedings of the Seventh Annual Conference on Evolutionary Programming, pages 591-600, 1998.
8
J. Kennedy and R.C. Eberhart.
A discrete binary version of the particle swarm algorithm.
In Proceedings of the World Multiconference on Systemics, Cybernetics and Informatics, pages 4104-4109, 1997.
12
Maurice Clerc.
Binary particle swarm optimisers: toolbox, derivations and mathematical insights.
http://clerc.maurice.free.fr/pso/binary_pso.
24
K. E. Parsopoulos and M. N. Vrahatis.
Particle swarm optimization method in multiobjective problems.
In Proceedings of the ACM Symposium on Applied Computing (SAC 2002), pages 603-607, 2002.
25
Carlos A. Coello and Maximino Salazar Lechuga.
Mopso: A proposal for multiple objective particle swarm optimization.
In Proceedings of the Congress on Evolutionary Computation (CEC'2002)), pages 1051-1056, 2002.
27
X. Li.
Adaptively choosing neighbourhood bests using species in a particle swarm optimizer for multimodal function optimization.
Lecture Notes on Computer Science, 3102:105-116, 2004.

 

Empirical Studies and Applications

7
Y. Shi and R.C. Eberhart.
Empirical study of particle swarm optimization.
In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), pages 1945-1950, 1999.
26
Yongde Zhang and Shabai Huang.
A novel multiobjective particle swarm optimization for buoys-arrangement design.
In Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT 2004), pages 24-30, 2004.

 

Modifications to the basic algorithm

19
T. M. Blackwell and Peter J. Bentley.
Dynamic search with charged swarms.
In Proceedings of the Genetic and Evolutionary Computation Conference 2002 (GECCO), pages 19-26, 2002.

20
P. N. Suganthan.
Particle swarm optimiser with neighbourhood operator.
In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), pages 1958-1962, 1999.

21
Riaan Brits.
Niching strategies for particle swarm optimization.
Master's thesis, University of Pretoria, Pretoria, 2002.

22
X. Hu and R.C. Eberhart.
Multiobjective optimization using dynamic neighborhood particle swarm optimisation.
In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), pages 1677-16, 2002.

23
J. Kennedy.
Stereotyping: improving particle swarm performance with cluster analysis.
In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), pages 1507-1512, 2000.

 

Full Bibliography

1
J. Kennedy, R.C. Eberhart, and Y. Shi.
Swarm intelligence.
Morgan Kaufmann Publishers, San Francisco, 2001.

2
K. E. Parsopoulos and M. N. Vrahatis.
Recent approaches to global optimization problems through particle swarm optimization.
Natural Computing: an international journal, 1(2-3):235-306, 2002.

3
Maurice Clerc and James Kennedy.
The particle swarm - explosion, stability, and convergence in a multidimensional complex space.
IEEE Trans. Evolutionary Computation, 6(1):58-73, 2002.

4
Frans van den Bergh.
An analysis of particle swarm optimizers.
PhD thesis, University of Pretoria, South Africa, 2002.

5
Ioan Cristian Trelea.
The particle swarm optimization algorithm: convergence analysis and parameter selection.
Inf. Process. Lett., 85(6):317-325, 2003.

6
Y. Shi and R.C. Eberhart.
Parameter selection in particle swarm optimization.
In Proceedings of the Seventh Annual Conference on Evolutionary Programming, pages 591-600, 1998.

7
Y. Shi and R.C. Eberhart.
Empirical study of particle swarm optimization.
In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), pages 1945-1950, 1999.

8
J. Kennedy and R.C. Eberhart.
A discrete binary version of the particle swarm algorithm.
In Proceedings of the World Multiconference on Systemics, Cybernetics and Informatics, pages 4104-4109, 1997.

9
Xiaohui Hu, Yuhui Shi, and Russ Eberhart.
Recent advances in particle swarm.
In Proceedings of IEEE Congress on Evolutionary Computation 2004 (CEC 2004), pages 90-97, 2004.

10
Shuyuan Yang, Min Wang, and Licheng Jiao.
A quantum particle swarm optimization.
In Proceedings of IEEE Congress on Evolutionary Computation 2004 (CEC 2004), pages 320-331, 2004.

11
Tiago Sousa, Arlindo Silva, and Ana Neves.
Particle swarm based data mining algorithms for classification tasks.
Parallel Comput., 30(5-6):767-783, 2004.

12
Maurice Clerc.
Binary particle swarm optimisers: toolbox, derivations and mathematical insights.
http://clerc.maurice.free.fr/pso/binary_pso.

13
J.H. Holland.
Adaptation.
Progress in theoretical biology, pages 263-293, 1976.

14
S. B. Thrun et al.
The MONK's problems: A performance comparison of different learning algorithms.
Technical Report CS-91-197, Pittsburgh, PA, 1991.

15
Shaun Saxon and Alwyn Barry.
XCS and the monk's problems.
In Wolfgang Banzhaf, Jason Daida, Agoston E. Eiben, Max H. Garzon, Vasant Honavar, Mark Jakiela, and Robert E. Smith, editors, Proceedings of the Genetic and Evolutionary Computation Conference, volume 1, page 809, Orlando, Florida, USA, 13-17 1999. Morgan Kaufmann.

16
Kenneth A. De Jong and William M. Spears.
Learning concept classification rules using genetic algorithms.
In Proceedings of the Twelfth International Conference on Artificial Intelligence (IJCAI), volume 2, 1991.

17
Steward W. Wilson.
Classifier fitness based on accuracy.
Evolutionary Computation, 3(2):149-175, 1995.

18
Ester Bernadó-Mansilla and Josep M. Garrell-Guiu.
Accuracy-based learning classifier systems: models, analysis and applications to classification tasks.
Evol. Comput., 11(3):209-238, 2003.

19
T. M. Blackwell and Peter J. Bentley.
Dynamic search with charged swarms.
In Proceedings of the Genetic and Evolutionary Computation Conference 2002 (GECCO), pages 19-26, 2002.

20
P. N. Suganthan.
Particle swarm optimiser with neighbourhood operator.
In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), pages 1958-1962, 1999.

21
Riaan Brits.
Niching strategies for particle swarm optimization.
Master's thesis, University of Pretoria, Pretoria, 2002.

22
X. Hu and R.C. Eberhart.
Multiobjective optimization using dynamic neighborhood particle swarm optimisation.
In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), pages 1677-16, 2002.

23
J. Kennedy.
Stereotyping: improving particle swarm performance with cluster analysis.
In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), pages 1507-1512, 2000.
24
K. E. Parsopoulos and M. N. Vrahatis.
Particle swarm optimization method in multiobjective problems.
In Proceedings of the ACM Symposium on Applied Computing (SAC 2002), pages 603-607, 2002.
25
Carlos A. Coello and Maximino Salazar Lechuga.
Mopso: A proposal for multiple objective particle swarm optimization.
In Proceedings of the Congress on Evolutionary Computation (CEC'2002)), pages 1051-1056, 2002.
26
Yongde Zhang and Shabai Huang.
A novel multiobjective particle swarm optimization for buoys-arrangement design.
In Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT 2004), pages 24-30, 2004.
27
X. Li.
Adaptively choosing neighbourhood bests using species in a particle swarm optimizer for multimodal function optimization.
Lecture Notes on Computer Science, 3102:105-116, 2004.
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