Particle Swarm Optimization Algorithm with a Bio-Inspired Aging Model

A Particle Swarm Optimization with a Bio-inspired Aging Model (BAM-PSO) algorithm is proposed to alleviate the premature convergence problem of other PSO algorithms. Each particle within the swarm is subjected to aging based on the age-related changes observed in immune system cells. The proposed algorithm is tested with several popular and well-established benchmark functions and its performance is compared to other evolutionary algorithms in both low and high dimensional scenarios. Simulation results reveal that at the cost of computational time, the proposed algorithm has the potential to solve the premature convergence problem that affects PSO-based algorithms; showing good results for both low and high dimensional problems. This work suggests that aging mechanisms do have further implications in computational intelligence.

[1]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[2]  Naturforschender Verein in Brünn.,et al.  Verhandlungen des naturforschenden Vereines in Brünn. , 1876 .

[3]  J. Deneubourg,et al.  Self-organized shortcuts in the Argentine ant , 1989, Naturwissenschaften.

[4]  R. Punnett,et al.  The Genetical Theory of Natural Selection , 1930, Nature.

[5]  Marco Dorigo,et al.  Ant colony optimization for continuous domains , 2008, Eur. J. Oper. Res..

[6]  Durbadal Mandal,et al.  PSO with aging leader and challengers for optimal design of high speed symmetric switching CMOS inverter , 2016, International Journal of Machine Learning and Cybernetics.

[7]  Marco Dorigo,et al.  Distributed Optimization by Ant Colonies , 1992 .

[8]  J. Neumann.  Zur Theorie der Gesellschaftsspiele , 1928 .

[9]  Guo Wei,et al.  On Line Parameter Identification of an Induction Motor Using Improved Particle Swarm Optimization , 2006, 2007 Chinese Control Conference.

[10]  Ying Lin,et al.  Particle Swarm Optimization With an Aging Leader and Challengers , 2013, IEEE Transactions on Evolutionary Computation.

[11]  Leandro Nunes de Castro,et al.  Fundamentals of natural computing: an overview , 2007 .

[12]  Alma Y. Alanis,et al.  Bio-inspired Aging Model Particle Swarm Optimization Neural Network Training for Solar Radiation Forecasting , 2014, CIARP.

[13]  P. Lansdorp,et al.  Extension of cell life-span and telomere length in animals cloned from senescent somatic cells. , 2000, Science.

[14]  Ajith Abraham,et al.  Hybrid Evolutionary Algorithms: Methodologies, Architectures, and Reviews , 2007 .

[15]  Jing J. Liang,et al.  Problem Definitions and Evaluation Criteria for the CEC 2005 Special Session on Real-Parameter Optimization , 2005 .

[16]  Ajith Abraham,et al.  Inter-particle communication and search-dynamics of lbest particle swarm optimizers: An analysis , 2012, Inf. Sci..

[17]  Nor Ashidi Mat Isa,et al.  Adaptive division of labor particle swarm optimization , 2015, Expert Syst. Appl..

[18]  George C. Williams,et al.  PLEIOTROPY, NATURAL SELECTION, AND THE EVOLUTION OF SENESCENCE , 1957, Science of Aging Knowledge Environment.

[19]  Wen-Bo Du,et al.  Particle Swarm Optimization with Scale-Free Interactions , 2014, PloS one.

[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]  Gisbert Schneider,et al.  Optimized Particle Swarm Optimization (OPSO) and its application to artificial neural network training , 2006, BMC Bioinformatics.

[23]  Michael N. Vrahatis,et al.  Particle Swarm Optimization and Intelligence: Advances and Applications , 2010 .

[24]  Francisco Herrera,et al.  A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms , 2011, Swarm Evol. Comput..

[25]  Xiaodong Li,et al.  Particle Swarm Optimizer with Aging Operator for Multimodal Function Optimization , 2013, Int. J. Comput. Intell. Syst..

[26]  J. M. Smith,et al.  The Logic of Animal Conflict , 1973, Nature.

[27]  Josef Kittler,et al.  Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications , 2015 .

[28]  Luigi Fortuna,et al.  Evolutionary Optimization Algorithms , 2001 .

[29]  R. A. Groeneveld,et al.  Practical Nonparametric Statistics (2nd ed). , 1981 .

[30]  C. Borror.  Practical Nonparametric Statistics, 3rd Ed. , 2001 .

[31]  J. L. Hayward,et al.  The Mathematics of Animal Behavior : An Interdisciplinary Dialogue , 2010 .

[32]  Russell C. Eberhart,et al.  Comparison between Genetic Algorithms and Particle Swarm Optimization , 1998, Evolutionary Programming.

[33]  A. Engelbrecht,et al.  A new locally convergent particle swarm optimiser , 2002, IEEE International Conference on Systems, Man and Cybernetics.

[34]  H. Gershon,et al.  The budding yeast, Saccharomyces cerevisiae, as a model for aging research: a critical review , 2000, Mechanisms of Ageing and Development.

[35]  Douglas H. Johnson.  The Insignificance of Statistical Significance Testing , 1999 .

[36]  Maurice Clerc,et al.  The particle swarm - explosion, stability, and convergence in a multidimensional complex space , 2002, IEEE Trans. Evol. Comput..

[37]  Christoph Wittmann,et al.  In-silico-driven metabolic engineering of Pseudomonas putida for enhanced production of poly-hydroxyalkanoates. , 2013, Metabolic engineering.

[38]  Mat IsaNor Ashidi,et al.  Adaptive division of labor particle swarm optimization , 2015 .

[39]  Alan S. Perelson,et al.  Effects of Aging on Influenza Virus Infection Dynamics , 2014, Journal of Virology.

[40]  Alma Y. Alanis,et al.  Bio-inspired Aging Model-Particle Swarm Optimization and Geometric Algebra for Structure from Motion , 2014, CIARP.

[41]  Guido Bacci.  Alcuni casi di inversione sessuale nei ricci di mare , 1954 .

[42]  Anatoli I Yashin,et al.  Age related changes in population of peripheral T cells: towards a model of immunosenescence , 2003, Mechanisms of Ageing and Development.

[43]  Linda Partridge,et al.  Benchmarks for ageing studies , 2007, Nature.