一種基于FPGA的自適應(yīng)遺傳算法
An FPGA Based Adaptive Genetic Algorithm
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摘要: 采用了一種適合硬件實現(xiàn)的自適應(yīng)遺傳算法，利用種群的最大適應(yīng)度fmax﹑最小適應(yīng)度fmin和適應(yīng)度平均值fave這3個變量來自適應(yīng)地控制整個種群的交叉概率pc 和變異概率pm 。選用了適合硬件實現(xiàn)的選擇﹑交叉﹑變異算子，并將它們設(shè)計成流水線結(jié)構(gòu), 同時，將選擇算子與適應(yīng)度計算并行化，大大提高了算法的運行效率。整個設(shè)計采用了XILINX公司的XC2V1000型號的FPGA芯片。算法利用VHDL語言來描述。實現(xiàn)后的測試表明，這種自適應(yīng)遺傳算法明顯改善了算法的搜索性能和全局收斂性，同時利用硬件實現(xiàn)有效減少了運行時間，使其在一些實時性要求較高的場合得到應(yīng)用成為可能。
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關(guān)鍵詞:
- 自適應(yīng)遺傳算法;并行; FPGA
Abstract: A hardware implement Adaptive Genetic Algorithm (AGA) is proposed in this paper. The adaptive algorithm uses three parameters, i. e. fmax , fmin and fave to determine the fc and fm of the whole generation adaptively. The selection , crossover and mutation operators which are suitable for hardware implement are selected and they are designed in a pipelining architecture . The parallelism of the selection operator and the computation of the fitness of the individual enhance the efficiency of the algorithm greatly. The hardware GA processor has been implemented in XILINX FPGA(Field Programmable Gate Arrays) XC2V1000. The VHDL language is used to describe the whole algorithm. Experimental results indicate that the adaptive genetic algorithm improves the global convergence and search performance of the algorithm greatly. The hardware implementation of the algorithm reduces the running time efficiently and makes it possible to apply in time-critical systems. -
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