| CFP |
Deadline |
| Call for papers- Particle Swarm Optimization: Advances and Applications |
31 March 2025 |
| Bibliography | ------------------------------------------------- |
| Swarm Intelligence: An Approach from Natural to Artificial (2023) | Kuldeep Singh Kaswan, Jagjit Singh Dhatterwal |
| Particle Swarm Optimization Algorithm and Its Applications: A Systematic Review (2022) | Gad, Ahmed G. |
| Applying Particle Swarm Optimization (2021) | Adıgüzel Mercangöz, Burcu (Ed.) |
| Particle Swarm Optimisation: Classical and Quantum Perspectives (2019) | Sun et al. |
| Metaheuristics (2017) | edited by Patrick Siarry |
| Search and Optimization by Metaheuristics (2016) | Du, Ke-Lin, Swamy, M. N. S. |
| Convergence Analysis for Particle Swarm Optimization | Berthold Immanuel Schmitt |
| Applications of Metaheuristics in Process Engineering (August 2014) | Jayaraman Valadi and Patrick Siarry (Eds) |
| Métaheuristiques, 2014 |
ouvrage coordonné par Patrick Siarry |
| Advances in Heuristic Signal Processing and Applications, 2013 |
Chatterjee, Amitava; Nobahari, Hadi; Siarry, Patrick (Eds.) |
| Evolutionary Optimization Algorithms, 2013 |
Dan Simon |
| Heuristics: Theory and Applications, 2013 |
edited by Patrick Siarry |
| Book: Hybrid metaheuristics, 2013 |
edited by El-Ghazali Talbi |
| Book: Metaheuristics for Dynamic Optimization, 2012 |
edited by Alba Enrique, Amir Nakib, & Patrick Siarry |
| Book: Integration of Swarm Intelligence and Artificial Neural Network, 2011 |
edited by Satchidananda Dehuri, Susmita Ghosh, & Sung-Bae Cho |
| Book: Theory of Randomized Search Heuristics, 2011 |
Foundations and Recent Developments edited by Anne Auger (INRIA, France) & Benjamin Doerr (Max-Planck-Institut fur Informatik, Germany) |
| Book: Swarm Stability and Optimization, 2011 |
Gazi, Veysel, Passino, Kevin M. |
| Book: Particle Swarm Optimization: Theory, Techniques and Applications, 2010 - 3rd Quarter | Andrea E. Olsson (Ed.) |
| Book: Particle Swarm Optimization and Intelligence: Advances and Applications, January 2010 |
Konstantinos E. Parsopoulos, and Michael N. Vrahatis |
| Biologically-inspired Optimisation Methods: Parallel Algorithms, Systems and Applications, August 2009 | Andrew Lewis et al. (Ed.) |
| Optimization in Signal and Image Processing, June 2009 | Patrick Siarry (Ed.) |
| A comparative study on PSO and GA for TSP, pp. 490-507, August 2009 | Mehmet Cunkas; M. Yasin Özsag lam |
| Book: Metaheuristics: from design to implementation, May 2009 | El-Ghazali Talbi |
| Book: Particle Swarm Optimization, March 2009 | The book is edited by Aleksandar Lazinica. It contains 29 chapters. Can be downloaded for free |
| Book: Multi-Objective Optimization in Computational Intelligence, March 2008 | Information Science Reference Two chapters about MOPSO: Chapter 2 - Multi-objective particle swarm optimization, K.E. Parsopoulos and M.N. Vrahatis Chapter 4 - Towards a More Efficient Multi-Objective Particle Swarm Optimizer, Luis V. Santana-Quintero, Noel Ramírez-Santiago and Carlos A. Coello Coello |
| XPS project technical reports | eXtended Particle Swarm project research papers (2004-2007) |
Building Virtual Reality Spaces for Visual Data Mining with Hybrid Evolutionary-Classical Optimization: Application to Microarray Gene Expression Data. Proceedings of the IASTED International Joint Conference on Artificial Intelligence and Soft Computing, ASC'2004, September 1-3, 2004, Marbella, Spain. ACTA Press, Anaheim, USA, pp 161-166. |
Julio Valdés |
| Book: Swarm Intelligence and Data Mining (Foreword by James Kennedy), Springer Verlag, 2006 | Ajith Abraham, Crina Grosan and Vitorino Ramos |
| Book: Fundamentals of Computational Swarm Intelligence, publishec by Wiley. Available on Amazon | Andries Angelbrecht |
| Book: Particle Swarm Optimization, published by ISTE, (direct link here) available also on Amazon. 2006 translation of the 2005 French book, with a few updates. | Clerc M. |
| "Repel the swarm to the optimum", Ed. Elsevier, Applied Mathematics and Computation 173 (2006) 265–272. available on ScienceDirect | A. Leontitsis, D. Kontogiorgos, J. Pagge |
| 2005 IEEE TEC award for a PSO paper! | |
| Particle Swarm Optimization for economic dispatch with security constraints, FLAIRS'04 Abstract |
ROHIT KUMAR PANCHOLI , K.S.SWARUP |
| An adaptive PSO algorithm for reactive power optimization, APSCOM (Advances in Power System Control Operation and Management), S6: Application of Artificial Intelligence Technique (part I), 11-14 November 2003, Hong Kong | Zhang, W., Liu, Y., Clerc M., |
| Optimal operating path for automated drilling operations by a new heuristic approach using PSO. International Journal of Production Research, Vol. 42, n°3, p.473-491, 2004 |
Onwubolu, G. Clerc M. |
| OLDER REFERENCES |
|
| Bibliography | By Yuhui Shi |
| Bibliography on Particle Swarm Optimization | By Ender Özcan |
| CS&E Fall '95 Seminar Abstracts | By Russell Eberhart. A concept for the optimization of nonlinear functions using particle swarm methodology is described. Implementations of two paradigms are discussed and compared. Benchmark testing of both paradigms is described, and applications, including nonlinear function optimization and neural network training, are discussed. Relationships between particle swarm optimization and both artificial life and genetic algorithms are reviewed. (not on line) |
| Computational Intelligence Developments and Applications | By James Kennedy and Russell Eberhart. Volume 4, Page 1942. A concept for the optimization of nonlinear functions using particle swarm methodology is introduced. The evolution of several paradigms is outlined, and an implementation of one of the paradigms is discussed. Benchmark testing of the paradigm is described, and applications, including nonlinear function optimization and neural network training, are proposed. The relationships between particle swarm optimization and both artificial life and genetic algorithms are described. Postscript file. |
| Computational Intelligence PC Tools | By Russell C. Eberhart, Roy W. Dobbins and Patrick K. Simpson Copyright 1996 Academic Press Professional ISBN 0-1222-8630-8 Chapter 6: Evolutionary Computation Implementations Includes implementations of a Genesis-like genetic algorithm and a particle swarm optimizer. (Software is on the diskette.) |
| NEL Seminars: Spring Semester 1996 | Wednesday, January 31: Cognition and Social Interaction: The Particle Swarm Algorithm. Discusses the hypothesis that precise reporting of individual and group performance, accomplished in human societies through the use of notation, is fundamental to the optimal adaptation of groups. Includes a PC demo. Speaker: Dr. Jim Kennedy, Social Psychologist, U.S. Bureau of Labor Statistics. |
| Socially Intelligent Agents Papers from the 1997 Fall Symposium | Minds and Cultures: Particle Swarm Implications, James Kennedy (not on line) |
| The particle swarm: Social adaptation of knowledge. Proceedings of the 1997 International Conference on Evolutionary Computation, Indianapolis, Indiana, IEEE Serice Center, Piscataway, NJ, 303-308 | By James Kennedy |
| 9th International Conference on Tools with Artificial Intelligence (ICTAI'97) | Using the Particle Swarm Optimization Technique to Train a Recurrent Neural Model , J. Salerno (not on line. Abstract) |
| Evolutionary Programming Conference 1998 | The Behavior of Particles 581, J. Kennedy Parameter Selection in Particle Swarm Optimization 591, Y. Shi and R.C. Eberhart Evolutionary Optimization Versus Particle Swarm Optimization: Philosophy and Performance Differences 601, P.J. Angeline Comparison between Genetic Algorithms and Particle Swarm Optimization 611, R.C. Eberhart and Y. Shi . |
| An Experimental Test of the Particle Swarm and Some Genetic Algorithms on the Multimodal Problem Generator | By James Kennedy and William M. Spears. In IEEE International Conference on Evolutionary Computation, pages 78-83, 1998. [The author warns that the PostScript for this paper was generated by Microsoft Word and may not be printable and/or displayable on some machines.]. Compressed PS file (53K) http://www.aic.nrl.navy.mil/~spears/papers/wcci98.ps.gz PDF file wcci98.pdf |
| Evolutionary optimization versus particle swarm optimization: Philosophy and performance differences. In V. W. Porto, Saravanan, N., Waagen, D., and Eiben, A. E. (Eds), Evolutionary Programming VII, 601, 610, Berlin, Springer | By Angeline, P. (1998) |
| Math stuff about Particle Swarm Optimization | By Maurice Clerc. On line papers and drafts of published/submitted papers and technical reports. Non classical PSO (adaptive, discrete/granular, combinatorialFuzzy). Contains also some presentations (HTML and PowerPoint) and C programs (quite often updated) |
| Parameter Selection in Particle Swarm Optimization | By Yuhui Shi and Russell C. Eberhart. In this paper, the authors first analyze the impact that the inertia weight and maximum velocity have on the performance of the particle swarm optimizer, and then provide guidelines for selecting these two parameters. Analysis of experiments demonstrates the validity of these guidelines. |
| Particle Swarm Optimization (From Proc. IEEE Int'l. Conf. on Neural Networks (Perth, Australia)) | By James Kennedy &Russell Eberhart. A concept for the optimization of nonlinear functions using particle swarm methodology is introduced. The evolution of several paradigms is outlined, and an implementation of one of the paradigms is discussed. Benchmark testing of the paradigm is described, and applications, including nonlinear function optimization and neural network training, are proposed. The relationships between particle swarm optimization and both artificial life and genetic algorithms are described. |
| Particle Swarm Optimiser with Neighbourhood Operator. Proceedings of the Congress on Evolutionary Computation 1999, p. 1958-1962 | By P. N. Suganthan |
| Training Product Units in Feedforward Neural Networks using Particle Swarm Optimization. Proceedings of the International Conference on Artificial Intelligence, Durban, South Africa, 1999, pp 36-40 | By A. Ismail, A. P. Engelbrecht |
| Application of Particle Swarm to Multiobjective Optimization, Department of Computer Science, Auburn University, 1999. PS file. | Moore J., Chapman R. |
| Adapting Particle Swarm Optimization to Dynamic Environments. International Conference on Artificial Intelligence, Monte Carlo Resort, Las Vegas, Nevada, USA | By Anthony Carlisle, Gerry Dozier |
| Comparing inertia weights and constriction factors in particle swarm optimization. Proceedings of the 2000 International Congress on Evolutionary Computation, San Diego, California, IEEE Service Center, Piscataway, NJ, 84-88 | By Eberhart, R.C., and Shi Y. |
| A Particle Swarm Optimization for Reactive Power and Voltage Control considering Voltage Security Assessment. IEEE Trans. on Power Systems, Vol. 15,No 4, pp. 1232-1239, November 2001, presented at IEEE PES Winter Meeting Columbus, Jan. 28-Feb. 1, 2001 | By H.Yoshida, K.Kawata, Y.Fukuyama, S.Takayama,&Y.Nakanishi |
| Practical Distribution State Estimation Using Hybrid Particle Swarm Optimization. Proceeding of IEEE Power Engineering Society Winter Meeting. January 28-February 1st, 2001. Columbus, Ohio, USA. |
By Shigenori Naka, Takamu Genji, Toshiki Yura, and Yoshikazu Fukuyama |
| Hybrid Particle Swarm Optimiser with Breeding and subpopulations. Proceedings of the third Genetic and Evolutionary Computation Conference (GECCO-2001). | By Løvbjerg, M., Rasmussen, T., K. and Krink, T. |
| Swarm Intelligence (book). Publisher Morgan Kaufmann Academic Press. 2001 | By James Kennedy and Russel Eberhart, with Yuhui Shi |
| Communication in Particle Swarm Optimization Illustrated by the Travelling Salesman Problem. Air Force Institute of Technology, 2001 | B. R. Secrest and G. B. Lamont |
| Engineering Design Optimization using a Swarm with an Intelligent Information Sharing among Individuals, Engineering Optimization (2001) | Ray, T., and Saini, P. |
| Several papers to download (IJCNN 2001, GECCO 2001, etc.) | Frans van den Bergh, and A.P Engelbrecht |
| Improving the fermentation medium for Echinocandin B production. Part II: Particle swarm optimization, in Process Biochemistry, vol. 36, 2001, pp. 661-669. | A. R. Cockshott and B. E. Hartman |
| Feature Selection for QSAR and QSPR Using Binary Particle Swarms, in Journal of Medicinal Chemistry , in press (2001-12). Abstract | Dimitris K. Agrafiotis and Walter Cedeño |
| Use of Intelligent-Particle Swarm Optimization in Electromagnetics, COMPUMAG Evian, July 2-5 2001, poster session B. | Gabriela Ciuprina, Daniel Ioan, Irina Muteanu |
| L'optimisation par essaim particulaire. Principes, modèles et usages. Hermès Science, Techniques et science informatiques, vol. 21, n° 7/2002, p. 941-964. | Maurice Clerc |
| "The Particle Swarm: Explosion, Stability, and Convergence in a Multi-Dimensional Complex Space", IEEE Transactions on Evolutionary Computation, 2002, vol. 6, p. 58-73. Abstract | Maurice Clerc, James Kennedy 2005 IEEE TEC award |
| "MOPSO: A Proposal for Multiple Objective Particle Swarm Optimization", Congress on Evolutionary Computation (CEC'2002), Piscataway, New Jersey, 2002, p. 1051-1056. | Coello Coello C. A., Salazar Lechuga M |
| "Multiobjective Optimization Using Dynamic Neighborhood Particle Swarm Optimization", Congress on Evolutionary Computation (CEC'2002), Piscataway, New Jersey, 2002, p. 1677-1681. | Hu X., Eberhart R. C. |
| "A swarm metaphor for Multiobjective Optimization", Engineering Optimization, vol. 2, iss. 34, 2002, p. 141-153. | Ray T., Liew K. M. |
| Adaptive particle swarm optimization: detection and response to dynamic systems. Proceedings of Congress on Evolutionary Computation, 2002. pp.1666-1670. Hawaii, USA. | X. Hu, and R. Eberhart |
| New Optimization Techniques in Enginering, in print, Springer-Verlag, 2003. Preface and Content. |
Onwubolu G. C., Babu B. V. |
| Chaotic dynamic characteristics in swarm intelligence • Article Applied Soft Computing, Volume 7, Issue 3, 1 June 2007, Pages 1019-1026 |
Liu, H.; Abraham, A.; Clerc, M. |