粒子群算法資源合輯

1、粒子群算法資源合輯0.Books and dissertations:Kennedy, J., Eberhart, R. C., and Shi, Y., Swarm intelligence San Francisco: M organ Kaufmann Publishers, 2001. (PSO的founders所著van den Bergh, Frans, "An analysis of particle swarm optimizers." PhD's Disser tation Department of Computer Science, Univer

2、sity of Pretoria, South Africa, 2 002. (Dr.Bergh的博士論文,詳盡的給出了他對(duì)PSO的分析和改進(jìn),建議通讀1.Papers1原始論文:Kennedy J,Eberhart R C. Particle Swarm Optimization C. Proceedings of IEEE I nternational Conference on Neural Networks, Perth, Australia, 1995.1942-1948.R. C. Eberhart and J. Kennedy, A new optimizer using par

3、ticle swarm theory,in Proc. 6th Int. Symp. Micromachine Human Sci., Nagoya,Japan, 19952理論基礎(chǔ):Clerc, M. and Kennedy, J., "The particle swarm-explosion, stability, and conve rgence in a multidimensional complex space," IEEE Transactions on Evolutionary Computation, vol. 6, no. 1, pp. 58-73, 2

4、002. (較完整的給出了PSO的收斂性,并發(fā)現(xiàn)使用壓縮因子可以保證收斂,04年IEEE Trans. EVC Best paper award,必讀Ozcan, E. and Mohan, C. K. Particle swarm optimization: surfing the waves. Pro ceedings of the IEEE Congress on Evolutionary Computation (CEC 1999, Washingt on, DC, USA. 1999Trelea, I. C., "The particle swarm optimizatio

5、n algorithm: convergence analysis and parameter selection," Information Processing Letters, vol. 85, no. 6, pp. 317-325, Mar.2003. (另一個(gè)較小的收斂分析3參數(shù)設(shè)置:Shi, Y. and Eberhart, R. C. Parameter selection in particle swarm optimization. Evolutionary Programming VII: Proceedings of the Seventh Annual Con

6、ference on Evolutionary Programming, New York. pp. 591-600, 1998Shi, Y. and Eberhart, R. C. Empirical study of particle swarm optimization. Pr oceedings of the IEEE Congress on Evolutionary Computation (CEC 1999, Piscata way, NJ. pp. 1945-1950, 1999 (主要是對(duì)慣性權(quán)重的試驗(yàn)Carlisle, A. and Dozier, G. An off-the

7、-shelf PSO. Proceedings of the Workshopon Particle Swarm Optimization 2001, Indianapolis, IN. 2001 (各個(gè)參數(shù)設(shè)置的比較,必讀4綜述:Eberhart, R. C. and Shi, Y. Comparison between genetic algorithms and particleswarm optimization. Evolutionary Programming VII: Proceedings of the Seventh Annual Conference on Evolutio

8、nary Programming, San Diego, CA. 1998 (GA與PSO比較Eberhart, R. C. and Shi, Y. Particle swarm optimization: developments, applications and resources. Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2001, Seoul, Korea. 2001Parsopoulos, K. E. and Vrahatis, M. N., "Recent approaches

9、to global optimization problems through particle swarm optimization," Natural Computing, vol. 1,no. 2-3, pp. 235-306, 2002. (很長(zhǎng)的綜述,但是比較偏重作者自己提出的幾個(gè)改進(jìn),呵呵5應(yīng)用:Ismail, A. and Engelbrecht, A. P. Training Product Units in Feedforward Neural Networks using Particle Swarm Optimization. Proceedings of th

10、e International Conference on Artificial Intelligence, Durban, South Africa. pp. 36-40, 1999van den Bergh, F. and Engelbrecht, A. P., "Cooperative learning in neural networks using particle swarm optimizers," South African Computer Journal, vol. 26pp. 84-90, 2000.L. Messerschmidt and A. P.

11、 Engelbrecht, Learning to play games using a PSO-based competitive learning approach, IEEE Trans. Evo l.Comput., vol. 8, pp. 280288, Jun. 2004.Settles, M. and Rylander, B. Neural network learning using particle swarm opti mizers. Advances in Information Science and Soft Computing, pp. 224-226, 2002T

12、illett, J. C., Rao, R., Sahin, F., and Rao, T. M. Cluster-head identificationin ad hoc sensor networks using particle swarm optimization. Proceedings of 2002 IEEE International Conference on Personal Wireless Communications, pp. 201-205, 2002Coello Coello, C. A., Luna, E. H. n., and Aguirre, A. H. n

13、. Use of particle swarm optimization to design combinational logic circuits. Lecture Notes in Computer Science(LNCS No. 2606, pp. 398-409, 2003# Tillett, J. C., Rao, R. M., Sahin, F., and Rao, T. M. Particle swarm optimization for the clustering of wireless sensors. Procedings of SPIE Vol. 5100: Dig

14、ital Wireless Communications V, pp. 73-83, 20036改進(jìn)與分析_離散域拓展及組合優(yōu)化:Kennedy, J. and Eberhart, R. C. A discrete binary version of the particle swarm algorithm. Proceedings of the World Multiconference on Systemics,Cyberneticsand Informatics 1997, Piscataway, NJ. pp. 4104-4109, 1997 (最早的離散PSO,非常聰明的改進(jìn),值得一

15、看Mohan, C. K. and Al-kazemi, B. Discrete particle swarm optimization. Proceedings of the Workshop on Particle Swarm Optimization 2001, Indianapolis, IN. 2001Laskari, E. C., Parsopoulos, K. E., and Vrahatis, M. N. Particle swarm optimization for integer programming. Proceedings of the IEEE Congress o

16、n Evolutionary Computation (CEC 2002, Honolulu, Hawaii USA. 2002 (PSO for 整數(shù)規(guī)劃Schoofs, L. and Naudts, B. Swarm intelligence on the binary constraint satisfaction problem. Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2002, Honolulu, Hawaii USA. 2002Wang, K.-P., Huang, L., Zhou, C

17、.-G., and Pang, W. Particle swarm optimizationfor traveling salesman problem. Proceedings of International Conference on Machine Learning and Cybernetics 2003, pp. 1583-1585, 2003 (引入幾個(gè)新算子,解決T SP問題Clerc, M., "Discrete Particle Swarm Optimization," New Optimization Techniquesin Engineering

18、Springer-Verlag, 2004. (Clerc大拿的DPSO,同樣引入了新算子7改進(jìn)與分析_參數(shù):Shi, Y. and Eberhart, R. C. A modified particle swarm optimizer. Proceedings of the IEEE Congress on Evolutionary Computation (CEC 1998, Piscataway, NJ. pp. 69-73, 1998 (慣性權(quán)重在此文中提出Clerc, M. The swarm and the queen: towards a deterministic and ad

19、aptive particle swarm optimization. Proceedings of the IEEE Congress on Evolutionary Comput ation (CEC 1999, pp. 1951-1957, 1999 (提出了queen的思想,里面還有個(gè)重力場(chǎng),比較有意思Eberhart, R. C. and Shi, Y. Comparing inertia weigthts and constriction factors in particle swarm optimization. Proceedings of the IEEE Congress

20、 on Evolutionary Computation (CEC 2000, San Diego, CA. pp. 84-88, 2000 (慣性權(quán)重與壓縮因子Shi, Y. and Eberhart, R. C. Particle swarm optimization with fuzzy adaptive inerita weight. Proceedings of the Workshop on Particle Swarm Optimization 2001, Indianapolis, IN. 2001 (為適應(yīng)動(dòng)態(tài)環(huán)境,提出模糊慣性權(quán)重A. Ra tnaweera, S. Hal

21、gamuge, and H. Watson, Self-organizing hierarchical par ticle swarm optimizer with time varying accelerating coefficients,IEEE Trans. Evol. Comput., vol. 8, pp. 240255, Jun. 2004. (對(duì)幾個(gè)參數(shù)做了拓展以及非常詳盡的分析8改進(jìn)與分析_粒子拓?fù)浞较?# Kennedy, J. Small worlds and mega-minds: effects of neighborhood topology on particle

22、 swarm performance. Proceedings of IEEE Congress on Evolutionary Comp utation (CEC 1999, Piscataway, NJ. pp. 1931-1938, 1999 (小世界拓?fù)鋵?duì)結(jié)果的影響Suganthan, P. N. Particle swarm optimiser with neighbourhood operator. Proceed ings of the IEEE Congress on Evolutionary Computation (CEC 1999, Piscataway, NJ. pp.

23、 1958-1962, 1999 (引入領(lǐng)域算子Kennedy, J. Stereotyping: improving particle swarm performance with cluster an alysis. Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2000 , San Diego, CA. pp. 1507-1512, 2000Kennedy, J. and Mendes, R. Population structure and particle swarm performance. Pr

24、oceedings of the IEEE Congress on Evolutionary Computation (CEC 2002, Hon olulu, Hawaii USA. 2002Krink, T., Vesterstroem, J. S., and Riget, J. Particle swarm optimisation with spatial particle extension. Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2002, Honolulu, Hawaii USA. 20

25、02Janson, S. and Middendorf, M. A hierarchical particle swarm optimizer. Proceed ings of IEEE Congress on Evolutionary Computation 2003 (CEC 2003, Canbella, A ustralia. pp. 770-776, 2003 (使粒子動(dòng)態(tài)的按照樹型排列Kennedy, J. and Mendes, R. Neighborhood topologies in fully-informed and best-of-neighborhood partic

26、le swarms. Proceedings of the 2003 IEEE International Wo rkshop on Soft Computing in Industrial Applications 2003 (SMCia/03, pp. 45-50, 2003R. Mendes, J. Kennedy, and J. Neves, The fully informed particle swarm: Simp ler, maybe better, IEEE Trans. Evol. Comput., vol. 8, pp. 204210, Jun. 2004. (重要的FI

27、Ps模型,所有粒子的信息用來更新一個(gè)粒子的信息9改進(jìn)與分析_多樣性提升方向:Blackwell, T. M. and Bentley, P. J. Don't push me! collision-avoiding swarms. Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2002, Honol ulu, Hawaii USA. 2002Riget, J. and Vesterstroem, J. S. A diversity-guided particle swarm optimizer- th

28、e ARPSO. Technical Report No. 2002-02. 2002. Dept. of Computer Science, Un iversity of Aarhus, EV ALife.Peram, T., Veeramachaneni, K., and Mohan, C. K. Fitness-distance-ratio based p article swarm optimization. Proceedings of the IEEE Swarm Intelligence Symposi um 2003 (SIS 2003, Indianapolis, India

29、na, USA. pp. 174-181, 2003comments:很多其他類里的paper都可以規(guī)類到這來.10改進(jìn)與分析_結(jié)合其他算法思想方向:Angeline, P. J. Using selection to improve particle swarm optimization. Procee dings of the IEEE Congress on Evolutionary Computation (CEC 1998, Anchorage, Alaska, USA. 1998 (借鑒GA里的選擇優(yōu)秀染色體思想L?vbjerg, M., Rasmussen, T. K., and Krink, T. Hyb