2010 International Conference on Field Programmable Logic and Applications 2010
DOI: 10.1109/fpl.2010.58
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FPGA Based Engines for Genetic and Memetic Algorithms

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Cited by 4 publications
(4 citation statements)
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“…Another approach is the steady-state GA, where the population is evolved by generating a single solution per iteration to replace an existing one. This approach requires less memory than the generation GA, and it can lead to efficient pipelined architectures [4].…”
Section: State Of the Artmentioning
confidence: 99%
“…Another approach is the steady-state GA, where the population is evolved by generating a single solution per iteration to replace an existing one. This approach requires less memory than the generation GA, and it can lead to efficient pipelined architectures [4].…”
Section: State Of the Artmentioning
confidence: 99%
“…Different hardware architectures can be explored by generating a single solution that replaces an existing one in the population at each generation [8]. This approach, called steady-state GA, requires less memory and leads to more efficient hardware pipelined architectures [9].…”
Section: B Hardware For Genetic Algorithmsmentioning
confidence: 99%
“…Subsequently, the missing cities in the child are filled in from the second parent, preserving their relative order. The hardware implementation of the MPX operator is based on a 4-stage pipelined architecture that is able to process a city each clock cycle [9].…”
Section: B Crossover and Fitness Calculationmentioning
confidence: 99%
“…Memetic algorithms (MA) (Eiben & Smith, 2003;Molina, Lozano & Herrera, 2010;Moscato, 1999;Santos & Alves, 2010) have been found to be effective for evolutionary computation (Areibi, Moussa & Abdullah, 2001;Merz & Freisleben, 1999). It can be viewed as the hybrid genetic algorithms (GA) (Eiben & Smith, 2003) consisting of local refinement to genetic search results.…”
Section: Introductionmentioning
confidence: 99%