DocumentCode :
727739
Title :
FPGA implementation of an adaptive genetic algorithm
Author :
Fang Mengxu ; Tang Bin
Author_Institution :
Chengdu Aeronaut. Polytech., Chengdu, China
fYear :
2015
fDate :
22-24 June 2015
Firstpage :
1
Lastpage :
5
Abstract :
In this paper, the adaptive genetic algorithm (AGA) is designed use Field Programmable Gate Array (FPGA) based on modular design. First, the FPGA´s internal structure and the basic design process are introduced, to Altera Cyclone III series chips as an example. Secondly algorithm of hardware and software environment is introduced. The software is Altera´s integrated development software, the Quartus II, development board is SOC/family experiment KX_7C series of experimental development system. Then the AGA is divided into some modules, such as fitness calculation module, control module, population initialization module, selection module, crossover and mutation module, data channel selection module, random number generator module, and memory module, etc. Finally the top-level module is downloaded to the Altera Cyclone III-EP3C40Q240C8N chip, and program is run out and debugged on the development board. Finally we compared the results of the hardware and software running.
Keywords :
field programmable gate arrays; genetic algorithms; random number generation; AGA; Altera Cyclone III series chips; Altera Cyclone III-EP3C40Q240C8N chip; FPGA; Quartus II; adaptive genetic algorithm; control module; crossover module; data channel selection module; field programmable gate array; fitness calculation module; memory module; mutation module; population initialization module; random number generator module; Biological cells; Field programmable gate arrays; Genetic algorithms; Hardware; Sociology; Software; Statistics; Altera Cyclone III-EP3C40Q240C8N; FPGA; adaptive genetic algorithm (AGA); modular design;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Service Systems and Service Management (ICSSSM), 2015 12th International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-4799-8327-8
Type :
conf
DOI :
10.1109/ICSSSM.2015.7170318
Filename :
7170318
Link To Document :
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