HGA: a hardware-based genetic algorithm
FPGA '95 Proceedings of the 1995 ACM third international symposium on Field-programmable gate arrays
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ASP-DAC '00 Proceedings of the 2000 Asia and South Pacific Design Automation Conference
Efficient and Accurate Parallel Genetic Algorithms
Efficient and Accurate Parallel Genetic Algorithms
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Pattern Recognition Letters
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Proceedings of the 3rd International Conference on Genetic Algorithms
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EH '00 Proceedings of the 2nd NASA/DoD workshop on Evolvable Hardware
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PARELEC '04 Proceedings of the international conference on Parallel Computing in Electrical Engineering
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IEEE Transactions on Evolutionary Computation
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This paper introduces a novel genetic algorithm whose features have been purposely designed to be suited to hardware implementation. This is distinct from previous hardware designs that have been realized directly from conventional genetic algorithm approaches. To be suitable for hardware implementation, we propose that a genetic algorithm should attempt to both minimize final layout dimensions and reduce execution time while remaining a valid implementation. Consequently, the new genetic algorithm specifically aims to keep the requisite silicon area to a minimum by incorporating a monogenetic strategy that retains only the optimal individual, resulting in a dramatic reduction in the memory requirement and obviating the need for crossover circuitry. The results given in this paper demonstrate that new approach improves on a number of existing hardware genetic algorithm implementations in terms of the quality of the solution produced, the calculation time and the hardware component requirements.