这种变换方法的基本思想来源于模拟退火过程（Simulated Annealing， SA），其中的系数4决定了选择的强制性，其值越小，原有目标函数值较高的 个体的适应度就越与其它个体的适应度...
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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.
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