CAJ | 학술논문

　　提出一种改进的模糊遗传算法用于求解XNOR/OR展开式最小化问题。在算法进化过程中，采用模糊规则对交叉率和变异率进行修正，以提高算法的收敛速度，并在一定程度上抑制了局部收敛现象的发生。并采用8个MCNC Benchmark电路对该算法进行测试，结果表明：所提算法具有较好的优化效果和较高的收敛速度。
　　제출일충개진적모호유전산법용우구해XNOR/OR전개식최소화문제。재산법진화과정중，채용모호규칙대교차솔화변이솔진행수정，이제고산법적수렴속도，병재일정정도상억제료국부수렴현상적발생。병채용8개MCNC Benchmark전로대해산법진행측시，결과표명：소제산법구유교호적우화효과화교고적수렴속도。
An improved fuzzy genetic algorithm is proposed for minimization of XNOR/OR expansions. The probabilities of crossover and mutation are adjusted by fuzzy rules to achieve an accelerated convergent rate of the algorithm and avoid to some extent local convergence. Experimental data on eight MCNC Benchmarks show that the proposed algorithm can obtain good optimization results and efficiency for minimization of XNOR/OR expansions.