模拟退火算法是一种用于解决连续、有序离散和多模态优化问题的随机优化技术。
SA is a stochastic optimization technique that has been used to solve continuous, order discrete and muti-modal optimization problems.
第二步是基于模型参数的图象分割算法，其核心是一个改进的多值模拟退火技术。
The second step is the image segmentation algorithm, whose key is the improved multiple-value simulated annealing technique.
研究基于直送的两阶段混合调度模型的模拟退火算法，其目标函数是最小化作业时间。
The paper studies the simulated annealing algorithm of two-stage hybrid scheduling model based on through transport, which the objective function is the minimized operation time.
本算法比遗传算法和模拟退火算法更适合于解决具有很多局部最小值的冗余传感器系统费用优化的问题，仿真实验结果表明本算法是很有效的。
It is more suitable than simulated annealing and genetic algorithms for solving the problem that presents many local minima. Experimental results show the method is efficient.
介绍了一种新的优化设计方法——模拟退火算法，其突出的优点是可以求得全局最优解。
The outstanding advantage of SA is that it can find the global optimum solution.
实验证明，改进的模拟退火算法是可行和有效的。
The simulation shows that the improved SAA is both feasible and efficient.
实验证明，改进的模拟退火算法是可行和有效的。
The simulation shows that the improved SAA is both feasible and efficient.
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