Magnetic particle swarm optimization

In this paper, we propose a new particle swarm approach based on the idea of repulsion by a magnetic field. The structure of the method is presented and, using a number of well-known benchmark functions in a 30-dimension search space, its performance is compared to that of well-established algorithms of similar inspiration. The global search potential of the proposal is also analyzed with the aid of a simpler simulation setup.

[1]  L.N. de Castro,et al.  An artificial immune network for multimodal function optimization , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[2]  Ellips Masehian,et al.  Particle Swarm Optimization Methods, Taxonomy and Applications , 2009 .

[3]  Paul A. Viola,et al.  MIMIC: Finding Optima by Estimating Probability Densities , 1996, NIPS.

[4]  David E. Goldberg,et al.  A Survey of Optimization by Building and Using Probabilistic Models , 2002, Comput. Optim. Appl..

[5]  Raghuveer M. Rao,et al.  Darwinian Particle Swarm Optimization , 2005, IICAI.

[6]  Qinghai Bai,et al.  Analysis of Particle Swarm Optimization Algorithm , 2010, Comput. Inf. Sci..

[7]  H. Mühlenbein,et al.  From Recombination of Genes to the Estimation of Distributions I. Binary Parameters , 1996, PPSN.

[8]  Hamed Ketabchi,et al.  Elitist Continuous Ant Colony Optimization Algorithm: Application to Reservoir Operation problems , 2006 .

[9]  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).

[10]  Shu-Cherng Fang,et al.  An Electromagnetism-like Mechanism for Global Optimization , 2003, J. Glob. Optim..

[11]  Romis Ribeiro Faissol Attux,et al.  Magnetic particle swarm optimization with estimation of distribution , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).

[12]  Feng Xia-ting.  Particle Swarm Optimization with Contracted Ranges of Both Search Space and Velocity , 2005 .

[13]  Jun Tang,et al.  Particle Swarm Optimization with Adaptive Mutation , 2009, 2009 WASE International Conference on Information Engineering.

[14]  Andries P. Engelbrecht,et al.  Computational Intelligence: An Introduction , 2002 .

[15]  Mauro Birattari,et al.  Swarm Intelligence , 2012, Lecture Notes in Computer Science.

[16]  Leandro Nunes de Castro,et al.  Fundamentals of Natural Computing - Basic Concepts, Algorithms, and Applications , 2006, Chapman and Hall / CRC computer and information science series.

[17]  Shu-Cherng Fang,et al.  On the Convergence of a Population-Based Global Optimization Algorithm , 2004, J. Glob. Optim..

[18]  David H. Wolpert,et al.  No free lunch theorems for optimization , 1997, IEEE Trans. Evol. Comput..

[19]  Xiao-Feng Xie,et al.  DEPSO: hybrid particle swarm with differential evolution operator , 2003, SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483).

[20]  Andries Petrus Engelbrecht,et al.  A Cooperative approach to particle swarm optimization , 2004, IEEE Transactions on Evolutionary Computation.

[21]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[22]  Shumeet Baluja,et al.  A Method for Integrating Genetic Search Based Function Optimization and Competitive Learning , 1994 .

[23]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[24]  Heinz Mühlenbein,et al.  Schemata, Distributions and Graphical Models in Evolutionary Optimization , 1999, J. Heuristics.

[25]  K. Price.  Differential evolution vs. the functions of the 2/sup nd/ ICEO , 1997, Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97).

[26]  Hou Zhi-rong,et al.  Particle Swarm Optimization with Adaptive Mutation , 2006 .

[27]  Qingfu Zhang,et al.  DE/EDA: A new evolutionary algorithm for global optimization , 2005, Inf. Sci..

[28]  R. Eberhart,et al.  Comparing inertia weights and constriction factors in particle swarm optimization , 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).

[29]  Kevin D. Seppi,et al.  The Kalman Swarm: A New Approach to Particle Motion in Swarm Optimization , 2004, GECCO.

[30]  Yuhui Shi,et al.  Particle swarm optimization: developments, applications and resources , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[31]  R. Storn,et al.  Differential Evolution - A simple and efficient adaptive scheme for global optimization over continuous spaces , 2004 .

[32]  D. Goldberg,et al.  BOA: the Bayesian optimization algorithm , 1999 .

[33]  M. Clerc,et al.  The swarm and the queen: towards a deterministic and adaptive particle swarm optimization , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).