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A New Model of Parallel Distributed Genetic Algorithms for Cluster Systems: Dual Individual DGAs

A New Model of Parallel Distributed Genetic Algorithms for Cluster Systems: Dual Individual DGAs. Tomoyuki HIROYASU Mitsunori MIKI Masahiro HAMASAKI Yusuke TANIMURA. Doshisha University Kyoto, Japan. Aim of this study. Optimization methods Finding the best routings of the network

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A New Model of Parallel Distributed Genetic Algorithms for Cluster Systems: Dual Individual DGAs

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  1. A New Model of Parallel Distributed Genetic Algorithms for Cluster Systems: Dual Individual DGAs Tomoyuki HIROYASU Mitsunori MIKI Masahiro HAMASAKI Yusuke TANIMURA Doshisha University Kyoto, Japan

  2. Aim of this study • Optimization methods • Finding the best routings of the network • Designing structures • Constructing systems New model of DGAs Genetic Algorithms Dual Individual DGAs (DGAs) • Island model (DGAs) • Master Slave • Cellular • Easy to divide into tasks in several ways • High searching ability

  3. High searching ability The high validity of the solutions because there are numbers of islands. Dual Individual DGAs (DuDGAs) DuDGA • There are two individuals in each island • Easiness to set up Crossover rate=1.0 Mutation rate= 0.5

  4. Parallerization of DuDGAs Selection Crossover Island Mutation Evaluation • In DuDGA, an island is moved by migraion.

  5. Test functions and used parameters • DuDGA and DGAs (4, 8, 12, 24 islands) are applied to each test function. Number of islands 120 4,8,12,24 F1=200bit Rastrigin F2=50bit Rosenbrock F3=100bit Griewank F4=100bit Ridge Population size 240 Migration rate 0.5 0.3 Migration interval 5 Crossover rate 1.0 Mutation rate 1/L Terminal condition After 5000 generation

  6. Test Functions Rastrigin Griewank Ridge Rosenbrok

  7. Cluster system for calculation Processor PentiumⅡ(Deschutes) Clock 400MHz # Processors 1 × 16 Main memory 128Mbytes × 16 Network Fast Ethernet (100Mbps) Communication TCP/IP, MPICH 1.1.2 OS Linux 2.2.10 Compiler gcc (egcs-2.91.61) Spec. of Cluster (16 nodes)

  8. Searching ability (covering rate) Covering rate( it is the success rate of finding the optimum of each problem in 20 trials.) 見 率 1.0 4 8 0.5 12 24 A DuDGA F1 F2 F3 F4 • DuDGA has high searching ability.

  9. 25 20 15 10 5 1 5 10 15 Distribution and parallel effects of DuDGAs Speed Up Rate The number of processors Speed up rate is the relation between the calculation time of one processor model and that of multi processor model. Therefore, this rate has the factor of the model distribution effects and the parallel effects of DuDGAs

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