Abstract
Research in Evolutionary Computation has switched some of its focus to applications in Electrical Engineering problems, leading to the field of study called Evolvable Hardware (EHW). The final goal is the creation of complete evolvable hardware systems that can adapt to changing environments and increase system performance during operation. To accomplish this task, there are three main components in this system: Genetic Algorithm, response evaluation and configurable hardware. Though the interpretation of the binary chromosome will vary from one optimization problem to another, the manipulation of the chromosomes using reproduction operators such as crossover and mutation will stay consistent. In this paper, we design a hardware-based architecture to perform the Genetic Algorithm in this system, called FPGA-based Genetic Algorithm Kernel. This modular architecture of the Genetic Algorithm will ensure its ease for modifications and suitability for different applications.
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Zhang, X., Shi, C., Hui, F. (2007). FPGA-Based Genetic Algorithm Kernel Design. In: Kang, L., Liu, Y., Zeng, S. (eds) Evolvable Systems: From Biology to Hardware. ICES 2007. Lecture Notes in Computer Science, vol 4684. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74626-3_40
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DOI: https://doi.org/10.1007/978-3-540-74626-3_40
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