Introducing recombination with dynamic linkage discovery to particle swarm optimization

In this paper, we introduce the recombination operator with the technique of dynamic linkage discovery to particle swarm optimization (PSO) in order to improve the performance of PSO. Numerical experiments are conducted on a set of carefully designed benchmark functions and demonstrate good performance achieved by the proposed methodology.

[1]  Jing J. Liang,et al.  Comprehensive learning particle swarm optimizer for global optimization of multimodal functions , 2006, IEEE Transactions on Evolutionary Computation.

[2]  Hillol Kargupta,et al.  The Gene Expression Messy Genetic Algorithm , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.

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

[4]  Hong-Chan Chang,et al.  Large-scale economic dispatch by genetic algorithm , 1995 .

[5]  Kalyanmoy Deb,et al.  Messy Genetic Algorithms: Motivation, Analysis, and First Results , 1989, Complex Syst..

[6]  David E. Goldberg,et al.  Genetic Algorithms and Walsh Functions: Part II, Deception and Its Analysis , 1989, Complex Syst..

[7]  Russell C. Eberhart,et al.  Parameter Selection in Particle Swarm Optimization , 1998, Evolutionary Programming.

[8]  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).

[9]  Jing J. Liang,et al.  Particle swarm optimization algorithms with novel learning strategies , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[10]  Jing J. Liang,et al.  Dynamic multi-swarm particle swarm optimizer with local search , 2005, 2005 IEEE Congress on Evolutionary Computation.

[11]  M. Pelikán,et al.  The Bivariate Marginal Distribution Algorithm , 1999 .

[12]  Yanchun Liang,et al.  Hybrid evolutionary algorithms based on PSO and GA , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[13]  Kalyanmoy Deb,et al.  RapidAccurate Optimization of Difficult Problems Using Fast Messy Genetic Algorithms , 1993, ICGA.

[14]  Dirk Thierens,et al.  Toward a Better Understanding of Mixing in Genetic Algorithms , 1993 .

[15]  David E. Goldberg,et al.  Genetic Algorithms and Walsh Functions: Part I, A Gentle Introduction , 1989, Complex Syst..

[16]  T.A.A. Victoire,et al.  Discussion of "Particle swarm optimization to solving the economic dispatch considering the generator constraints" , 2004 .

[17]  Peter J. Angeline,et al.  Evolutionary Optimization Versus Particle Swarm Optimization: Philosophy and Performance Differences , 1998, Evolutionary Programming.

[18]  G. Sheblé,et al.  Genetic algorithm solution of economic dispatch with valve point loading , 1993 .

[19]  G. Harik Linkage Learning via Probabilistic Modeling in the ECGA , 1999 .

[20]  David E. Goldberg,et al.  Modified Linkage Learning Genetic Algorithm For Difficult Non-stationary Problems , 2002, GECCO.

[21]  E. Wilson,et al.  Sociobiology: The New Synthesis , 1975 .

[22]  T. Jayabarathi,et al.  Evolutionary programming techniques for different kinds of economic dispatch problems , 2005 .

[23]  David E. Goldberg,et al.  Introducing Start Expression Genes to the Linkage Learning Genetic Algorithm , 2002, PPSN.

[24]  James Kennedy,et al.  The particle swarm: social adaptation of knowledge , 1997, Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97).

[25]  Joong-Rin Shin,et al.  A particle swarm optimization for economic dispatch with nonsmooth cost functions , 2005, IEEE Transactions on Power Systems.

[26]  Whei-Min Lin,et al.  An Improved Tabu Search for Economic Dispatch with Multiple Minima , 2002, IEEE Power Engineering Review.

[27]  David E. Goldberg,et al.  Linkage Identification by Non-monotonicity Detection for Overlapping Functions , 1999, Evolutionary Computation.

[28]  Ulf Grenander,et al.  A stochastic nonlinear model for coordinated bird flocks , 1990 .

[29]  Gilbert Syswerda,et al.  Simulated Crossover in Genetic Algorithms , 1992, FOGA.

[30]  Craig W. Reynolds Flocks, herds, and schools: a distributed behavioral model , 1987, SIGGRAPH.

[31]  A. Ebenezer Jeyakumar,et al.  Hybrid PSO–SQP for economic dispatch with valve-point effect , 2004 .

[32]  A. E. Eiben,et al.  Genetic algorithms with multi-parent recombination , 1994, PPSN.

[33]  Ying-ping Chen,et al.  Extending the Scalability of Linkage Learning Genetic Algorithms: Theory and Practice , 2004 .

[34]  G. Harik Learning gene linkage to efficiently solve problems of bounded difficulty using genetic algorithms , 1997 .

[35]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[36]  A. Kai Qin,et al.  Self-adaptive differential evolution algorithm for numerical optimization , 2005, 2005 IEEE Congress on Evolutionary Computation.

[37]  David E. Goldberg,et al.  Learning Linkage , 1996, FOGA.

[38]  David E. Goldberg,et al.  Genetic Algorithm Design Inspired by Organizational Theory: Pilot Study of a Dependency Structure Matrix Driven Genetic Algorithm , 2003, GECCO.

[39]  Y. Rahmat-Samii,et al.  Particle swarm, genetic algorithm, and their hybrids: optimization of a profiled corrugated horn antenna , 2002, IEEE Antennas and Propagation Society International Symposium (IEEE Cat. No.02CH37313).

[40]  Nikolaus Hansen,et al.  A restart CMA evolution strategy with increasing population size , 2005, 2005 IEEE Congress on Evolutionary Computation.

[41]  Russell C. Eberhart,et al.  Multiobjective optimization using dynamic neighborhood particle swarm optimization , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[42]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[43]  Masaharu Munetomo,et al.  Linkage Identification by Nonlinearity Check for Real-Coded Genetic Algorithms , 2004, GECCO.

[44]  Thomas Kiel Rasmussen,et al.  Hybrid Particle Swarm Optimiser with breeding and subpopulations , 2001 .

[45]  G. Sheblé,et al.  Refined genetic algorithm-economic dispatch example , 1995 .

[46]  Murat Uzam,et al.  Economic dispatch solution using a genetic algorithm based on arithmetic crossover , 2001, 2001 IEEE Porto Power Tech Proceedings (Cat. No.01EX502).

[47]  David E. Goldberg,et al.  The Design of Innovation: Lessons from and for Competent Genetic Algorithms , 2002 .

[48]  Hong-Tzer Yang,et al.  Evolutionary programming based economic dispatch for units with non-smooth fuel cost functions , 1996 .

[49]  Kalyanmoy Deb,et al.  Messy Genetic Algorithms Revisited: Studies in Mixed Size and Scale , 1990, Complex Syst..

[50]  Dirk Thierens,et al.  Linkage Information Processing In Distribution Estimation Algorithms , 1999, GECCO.

[51]  Allen J. Wood,et al.  Power Generation, Operation, and Control , 1984 .

[52]  Russell C. Eberhart,et al.  A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.

[53]  Terence Soule,et al.  Breeding swarms: a GA/PSO hybrid , 2005, GECCO '05.

[54]  Chilukuri K. Mohan,et al.  Particle swarm optimization with adaptive linkage learning , 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

[55]  Philip G. Hill,et al.  Power generation , 1927, Journal of the A.I.E.E..

[56]  Saku Kukkonen,et al.  Real-parameter optimization with differential evolution , 2005, 2005 IEEE Congress on Evolutionary Computation.

[57]  D. Goldberg,et al.  Escaping hierarchical traps with competent genetic algorithms , 2001 .

[58]  Pedro J. Ballester,et al.  Real-parameter optimization performance study on the CEC-2005 benchmark with SPC-PNX , 2005, 2005 IEEE Congress on Evolutionary Computation.

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

[60]  S. Baskar,et al.  Hybrid real coded genetic algorithm solution to economic dispatch problem , 2003, Computers & electrical engineering.

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

[62]  Kalyanmoy Deb,et al.  Analyzing Deception in Trap Functions , 1992, FOGA.

[63]  J. Yuryevich,et al.  Evolutionary-programming-based algorithm for environmentally-constrained economic dispatch , 1998 .

[64]  Jim Smith,et al.  An Adaptive Poly-Parental Recombination Strategy , 1995, Evolutionary Computing, AISB Workshop.

[65]  Zwe-Lee Gaing,et al.  Particle swarm optimization to solving the economic dispatch considering the generator constraints , 2003 .

[66]  James Kennedy,et al.  Small worlds and mega-minds: effects of neighborhood topology on particle swarm performance , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).