摘要
针对嵌入式系统软硬件划分问题,在比较了遗传算法(GA)和模拟退火(SA)各自优缺点的基础上,提出了采用遗传/模拟退火混合算法(GASA)的策略。该算法的核心思想是将模拟退火算法嵌入到遗传算法中,利用遗传优化算法的结果来制约模拟退火的随机状态产生,然后根据模拟退火算法的接受准则和随机状态产生函数来更新遗传算法的种群,从而最终得到最优解。与单纯的遗传算法和模拟退火算法进行对比实验,实验结果表明,GASA更有优势,得到的划分结果也更优秀。
To solve the hardware/software partitioning problem in embedded system,based on the comparison of Genetic Algorithm（GA） and Simulated Annealing（SA）,a hybrid algorithm is proposed on the basis of Genetic Algorithm and Simulated Annealing,which combines the merits of the two algorithms.The essence of the algorithm is inserting Simulated Annealing to Genetic Algorithm.On one hand,the result of Genetic Algorithm restricts the forming of the random state,and on the other hand,the function,formed in Simulated Annealing according to the accepting criterion and random state,updates the population for Genetic Algorithm.Experimental results indicate that the hybrid algorithm is superior to the pure GA and SA in ability and gets better portioning results.
出处
《计算机工程与应用》
CSCD
北大核心
2010年第28期73-76,共4页
Computer Engineering and Applications
关键词
嵌入式系统
软硬件划分
遗传算法
模拟退火
embedded system
hardware/software partitioning
genetic algorithm
simulated annealing
