文中根据混合离散变量的特点，提出了几种邻域状态的产生函数和迭代方案，给出了适宜的模拟退火过程的冷却进度表。
According to the property of mixed-discrete variable problem, an adjacent producing function states is proposed, and a suitable annealing schedule to this optimzation is given.
在寻优过程中，通过不断衰减混沌扰动幅度及混沌扰动的接受概率来实现混沌的模拟退火。
During the process of optimization, chaos simulated annealing was realized by decaying the amplitude of the chaos noise and the probability of accepting continuously.
算法引入模拟退火机制，在遗传进化过程中的每一代，对最优个体进行邻域局部寻优，利用模拟退火进一步改善算法的收敛性能。
Simulated annealing mechanism is introduced to do local-search for the best chromosome in every generation of the evolution process. This improves the convergence of the algorithm.
利用模拟退火方法研究非对称半结晶两嵌段共聚物熔体分别在弱分离和强分离条件下的结晶过程。
A simulated annealing method is used to study the micro phase separation and crystallization in cylinder-forming semicrystalline diblock copolymers.
研究了模拟退火算法在解决问题过程中存在的过早收敛问题并分析了其原因，提出了相应的改进方案。
It put its most attention on stressing the fast-convergence problem during the process of sa, its causation and the ameliorative scheme.
其中在模拟退火算法的设计过程中，使用当前运行状况干预新解的生成过程，使得优化计算收敛加快。
During algorithm design on SA, the performance of current solution affects direction of new solution generates, this improves the efficient of the calculation.
为了增强情感识别过程中皮肤电反应(GSR)信号特征选择的有效性，提出了一种改进的模拟退火免疫粒子群算法。
An improved immune particle swarm optimization was presented in this study in order to increase the effectiveness of feature selection for emotion recognition based on Galvanic Skin Response (GSR).
为了增强情感识别过程中皮肤电反应(GSR)信号特征选择的有效性，提出了一种改进的模拟退火免疫粒子群算法。
An improved immune particle swarm optimization was presented in this study in order to increase the effectiveness of feature selection for emotion recognition based on Galvanic Skin Response (GSR).
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