For function optimization problems, according to the nature of the objective function domain, can be divided into discrete function optimization and continuous function optimization.
对于函数优化这个问题，根据目标函数定义域的性质，可以分为离散函数最优化和连续函数最优化。
Then, we consider a new filled function method with parameter free for solving general global optimization problems.
然后，对于一般结构的全局优化问题，我们给出了一个新的无参数的填充函数方法。
In this paper, a filled function method for solving global optimization problems with inequality and equality constraints is proposed.
提出了一种解决含有等式约束及不等式约束的全局优化问题的填充函数方法。
A new filled function with one parameter is used to find a global minimizer for unconstrained global optimization problems.
考虑用单参数填充函数求解无约束全局优化问题。
The convergence property and dynamic characteristics of the newly proposed population migration algorithm for solving global function optimization problems are analyzed by means of probability.
用概率论分析了新提出的求解函数全局优化问题的人口迁移算法的收敛性及动态特性。
The convergence property and dynamic characteristics of the newly proposed population migration algorithm for solving global function optimization problems are analyzed by means of probability.
用概率论分析了新提出的求解函数全局优化问题的人口迁移算法的收敛性及动态特性。
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