Volume 27 Issue 06
May  2015
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Ran Huanhuan, Pan Xudong, Tian Junlin. Research on evolvable hardware based on population hybridization Monkey-King genetic algorithm[J]. High Power Laser and Particle Beams, 2015, 27: 061006. doi: 10.11884/HPLPB201527.061006
Citation: Ran Huanhuan, Pan Xudong, Tian Junlin. Research on evolvable hardware based on population hybridization Monkey-King genetic algorithm[J]. High Power Laser and Particle Beams, 2015, 27: 061006. doi: 10.11884/HPLPB201527.061006

Research on evolvable hardware based on population hybridization Monkey-King genetic algorithm

doi: 10.11884/HPLPB201527.061006
  • Received Date: 2015-01-09
  • Rev Recd Date: 2015-03-20
  • Publish Date: 2015-05-26
  • The evolution hardware as a new hardware carrier, having self-organizing, adaptive, self-repair ability, is an important application of artificial intelligence in the controller of high energy laser. Genetic algorithm is one of the important factors that influence the hardware evolution speed. For the problems of long evolutionary time and large amount of computation of traditional genetic algorithm, an improved genetic algorithmPopulation Hybridization Monkey-King Genetic Algorithm (PHMKGA)was proposed. Inspired by hybrid vigor in biological species, gene sequences in the PHMKGA were divided into Nd independent evolution sub populations while evolving. Each sub population was formed by evolving according to Monkey-King Genetic Algorithm from the original population; the Monkey king genes of sub populations were exchanged to be repeated Monkey King genetic operation; the offsprings of heterosis were produced in sub population. Analysis shows that the PHMKGA(Nd is the number of sub population)could reduce the computation of gene ordering in each generation to 1/Nd comparing to Monkey-King Genetic Algorithm, and is more conducive to the realization of parallel. The simulation analysis based on MATLAB and Modelsim indicates that the PHMKGA results in faster convergence speed and better evolution.
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