Parameter Setting in Parallel Genetic Algorithms

Parallel genetic algorithms (GAs) have numerous parameters that affect their efficiency and accuracy. Traditionally, these parameters have been studied using empirical studies whose generality and limitations are difficult to assess. This chapter reviews existing theoretical models that predict the effects of the parameters. The models are used to examine the effect of communication topologies, migration rates, population sizing, and the choice of migrants and the individuals they replace in the receiving populations. The models should help practitioners make informed decisions about the setting of parameters of parallel GAs.

[1]  William W. Hargrove,et al.  MECHANISTIC-BASED GENETIC ALGORITHM SEARCH ON A BEOWULF CLUSTER OF LINUX PCS , 2000 .

[2]  Kenneth A. De Jong,et al.  An Analysis of Local Selection Algorithms in a Spatially Structured Evolutionary Algorithm , 1997, ICGA.

[3]  Susan E. Conry,et al.  An agent-oriented, massively distributed parallelization model of evolutionary algorithms , 1999 .

[4]  Reiko Tanese,et al.  Distributed Genetic Algorithms , 1989, ICGA.

[5]  Marc Parizeau,et al.  The Master-Slave Architecture for Evolutionary Computations Revisited , 2003, GECCO.

[6]  David E. Goldberg,et al.  Efficient Parallel Genetic Algorithms: Theory and Practice , 2000 .

[7]  Martina Gorges-Schleuter,et al.  Explicit Parallelism of Genetic Algorithms through Population Structures , 1990, PPSN.

[8]  Enrique Alba,et al.  Modeling Selection Intensity for Toroidal Cellular Evolutionary Algorithms , 2004, GECCO.

[9]  Takeshi Yamada,et al.  The ECOlogical Framework II : Improving GA Performance At Virtually Zero Cost , 1993, ICGA.

[10]  Kenneth de Jong,et al.  The behavior of spatially distributed evolutionary algorithms in non-stationary environments , 1999 .

[11]  Heinz Mühlenbein,et al.  Evolution in Time and Space - The Parallel Genetic Algorithm , 1990, FOGA.

[12]  Reiko Tanese,et al.  Parallel Genetic Algorithms for a Hypercube , 1987, ICGA.

[13]  Bernard P. Zeigler,et al.  Asynchronous Genetic Algorithms on Parallel Computers , 1993, ICGA.

[14]  E. Cant.  Migration Policies and Takeover Times in Parallel Genetic Algorithms , 1999 .

[15]  Enrique Alba,et al.  Comparing Synchronous and Asynchronous Cellular Genetic Algorithms , 2002, PPSN.

[16]  J. Sprave.  A unified model of non-panmictic population structures in evolutionary algorithms , 1999 .

[17]  Erik D. Goodman,et al.  Investigating Parallel Genetic Algorithms on Job Shop Scheduling Problems , 1997, Evolutionary Programming.

[18]  Erick Cantú-Paz,et al.  Migration Policies, Selection Pressure, and Parallel Evolutionary Algorithms , 2001, J. Heuristics.

[19]  Patrice Roger Calégari.  Parallelization of population-based evolutionary algorithms for combinatorial optimization problems , 1999 .

[20]  Erick Cantú-Paz,et al.  Selection Intensity in Genetic Algorithm with Generation Gaps , 2000, GECCO.

[21]  Scott B. Baden,et al.  Analysis of the numerical effects of parallelism on a parallel genetic algorithm , 1996, Proceedings of International Conference on Parallel Processing.

[22]  G. Rudolph.  On Takeover Times in Spatially Structured Populations : Array and Ring , 2001 .

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

[24]  David E. Goldberg,et al.  Predicting Speedups of Ideal Bounding Cases of Parallel Genetic Algorithms , 1997, ICGA.

[25]  Kenneth A. De Jong,et al.  An Analysis of the Effects of Neighborhood Size and Shape on Local Selection Algorithms , 1996, PPSN.

[26]  Erick Cantú-Paz,et al.  Efficient and Accurate Parallel Genetic Algorithms , 2000, Genetic Algorithms and Evolutionary Computation.

[27]  George G. Robertson,et al.  Parallel Implementation of Genetic Algorithms in a Classifier Rystem , 1987, ICGA.

[28]  William B. Langdon,et al.  Java based Distributed Genetic Programming on the Internet , 1999, GECCO.

[29]  E. Cantu-Paz,et al.  The Gambler's Ruin Problem, Genetic Algorithms, and the Sizing of Populations , 1997, Evolutionary Computation.

[30]  L. Darrell Whitley,et al.  Serial and Parallel Genetic Algorithms as Function Optimizers , 1993, ICGA.

[31]  Erik D. Goodman,et al.  Coarse-grain parallel genetic algorithms: categorization and new approach , 1994, Proceedings of 1994 6th IEEE Symposium on Parallel and Distributed Processing.

[32]  Martina Gorges-Schleuter,et al.  An Analysis of Local Selection in Evolution Strategies , 1999, GECCO.

[33]  Erick Cant.  Using Markov Chains to Analyze a Bounding Case of Parallel Genetic Algorithms , 2007 .

[34]  D. WhitleyComputer.  A Free Lunch Proof for Gray versus Binary Encodings , 1999 .

[35]  W. Hart.  Adaptive global optimization with local search , 1994 .

[36]  John R. Koza,et al.  Building a Parallel Computer System for $18, 000 that Performs a Half Peta-Flop per Day , 1999, GECCO.

[37]  Enrique Alba,et al.  Parallelism and evolutionary algorithms , 2002, IEEE Trans. Evol. Comput..

[38]  Kalyanmoy Deb,et al.  Genetic Algorithms, Noise, and the Sizing of Populations , 1992, Complex Syst..

[39]  Joel E. Hirsh,et al.  Evolutionary Programming Strategies with Self-Adaptation Applied to the Design of Rotorcraft Using Parallel Processing , 1998, Evolutionary Programming.

[40]  David H. Bailey.  Misleading Performance Reporting in the Supercomputing Field , 1992, Sci. Program..

[41]  D. Fogel.  Evolutionary algorithms in theory and practice , 1997, Complex..

[42]  Bernard Manderick,et al.  A Massively Parallel Genetic Algorithm: Implementation and First Analysis , 1991, ICGA.

[43]  L. Darrell Whitley,et al.  GENITOR II: a distributed genetic algorithm , 1990, J. Exp. Theor. Artif. Intell..

[44]  Günter Rudolph,et al.  A cellular genetic algorithm with self-adjusting acceptance threshold , 1995 .

[45]  Trevor N. Mudge,et al.  A Parallel Genetic Algorithm for Multiobjective Microprocessor Design , 1995, ICGA.

[46]  Heinz Mühlenbein,et al.  The Science of Breeding and Its Application to the Breeder Genetic Algorithm (BGA) , 1993, Evolutionary Computation.

[47]  Dirk Thierens,et al.  Mixing in Genetic Algorithms , 1993, ICGA.

[48]  Brian D. Davison,et al.  Effect of Global Parallelism on a Steady State GA 1 , 1999 .

[49]  Erick Cantú-Paz,et al.  Markov chain models of parallel genetic algorithms , 2000, IEEE Trans. Evol. Comput..

[50]  Kalyanmoy Deb,et al.  A Comparative Analysis of Selection Schemes Used in Genetic Algorithms , 1990, FOGA.

[51]  D. Goldberg,et al.  Predicting Speedups of Idealized Bounding Cases of Parallel Genetic Algorithms , 1997 .

[52]  David G. Green,et al.  An Empirical Investigation of Optimization in Dynamic Environments Using the Cellular Genetic Algorithm , 2000, GECCO.

[53]  Thomas Bäck,et al.  Parallel Optimization of Evolutionary Algorithms , 1994, PPSN.

[54]  Enrique Alba,et al.  A survey of parallel distributed genetic algorithms , 1999, Complex..

[55]  Bernard Manderick,et al.  Fine-Grained Parallel Genetic Algorithms , 1989, ICGA.

[56]  Erick Cantú-Paz,et al.  Modeling Idealized Bounding Cases of Parallel Genetic Algorithms , 1996 .

[57]  Theodore C. Belding,et al.  The Distributed Genetic Algorithm Revisited , 1995, ICGA.