A new approach is presented to handle constraints optimization using evolutionary algorithms.
提出了一种求解约束函数优化问题的方法。
Having no distinctly guided tendency is one of the main weaknesses of Evolutionary Algorithms.
进化算法的一个很大的不足是个体进化本身没有一个明确的引导趋势。
Analysis and discussion are carried out on the existing multiobjective evolutionary algorithms.
对已有的多目标进化算法的收敛性及算法性能进行了分析与讨论。
The computational time complexity is an important topic in the theory of evolutionary algorithms.
计算时间复杂性是演化理论中的一个重大课题。
The paper realizes the sorting of radar signal by the ANN based on immune evolutionary algorithms.
介绍采用基于免疫进化算法的神经网络对雷达信号分选的实现方法。
By using real number coding chromosome representation, two evolutionary algorithms to TSP are designed.
采用实数编码的染色体表示方式，先后自行设计实现了两种演化算法求解tsp问题。
This paper is to study the use of evolutionary algorithms to solve multi-objective optimization problem.
本文主要是研究用进化算法来解决多目标优化问题。
A framework for developing CI algorithms such as particle swarms, evolutionary algorithms, neural networks etc.
它是用于开发CI算法的一个框架，可以开发如粒子密集度，进化算法，神经网络等。
A general approach based on evolutionary algorithms to inverse parameter identification problems of PDEs is introduced.
给出了一种利用演化计算方法求解微分方程中的参数识别类型反问题的方法。
We presented a general methodology based on evolutionary algorithms (EAs) for the parameter estimation of inverse problems.
给出了一种利用演化计算方法求解微分方程中的参数识别类型反问题的方法。
Ant system algorithm is a kind of evolutionary algorithms, which is efficient in solving combinatorial optimization problem.
蚁群算法是一种进化算法，适合解决组合优化问题，指派问题是组合优化问题中的一个分支。
This is a kind of optimization technology, which is of great value to introduction of evolutionary algorithms to data mining.
在数据挖掘中引入进化算法具有相当的现实意义。
Finally, evolutionary programming which is the representation of evolutionary algorithms compares with other evolutionary algorithms.
最后，以进化规划为进化算法的代表，对其区别加以分析。
Evolutionary algorithm called evolutionary algorithms is a kind of stochastic optimization methods by simulating natural evolutionary process.
进化算法也称演化算法，是一种模拟自然进化过程的随机优化方法。
It is similar in some ways to genetic algorithms or evolutionary algorithms, but requires less computational cost and generally only a few lines of code.
这种算法在有些地方与遗传算法或竞争算法相类似，但是计算量更小，而且源程序更简单。
QEA is more suitable for parallel structure than the conventional evolutionary algorithms because of rapid convergence and good global search capability.
此外，量子进化算法具有收敛快和好的全局搜索特性，因此它比传统的进化算法更适于并行结构的实现。
Evolutionary algorithms give a new sign and new resolution to these problem with its special natural evolutionary law and population optimization technology.
进化算法以其独特的按自然进化法则、群体优化搜索的优越性，为上述问题的解决提供了新思想和新途径。
The drawbacks of simulated evolutionary algorithms are that the global optimality can not be always guaranteed because of randomicity and premature con vergence.
具体表现在：由于模拟进化算法的随机性，不能保证每次计算都能收敛到全局最优解，同时还存在“早熟”现象；
The result shows that it is better than other existing evolutionary algorithms in search efficiency, range of applications, accuracy and robustness of solutions.
仿真结果表明该算法在搜索效率、应用范围、解的精确性和鲁棒性上都优于其他现存演化算法。
Probabilistic modeling evolutionary algorithms (PMEAs) that incorporate building models into evolutionary algorithms have become a new class of evolutionary algorithms.
概率分析进化算法是将构造性模型引入进化算法进行研究而形成的一类新型进化算法。
A real factorization method based on evolutionary algorithms is proposed for finding tbe roots of the characteristic equation of a linear time-invariant closed-loop system.
针对线性定常闭环系统特征方程的求根问题，提出了一种基于演化算法的实因式分解法。
Estimation of Distribution algorithms (EDAs) are new evolutionary algorithms based on probabilistic model and have become a new focus in the field of evolutionary computation.
分布估计算法由于其较强的理论基础已成为进化计算研究的新热点。
That is, we will demonstrate how the evolutionary game can be embodied using co-evolutionary algorithms and also confirm whether it can reach the optimal equilibrium point of a MOP.
且说明进化游戏如何由共同进化算法来具体实现，证实它是否能达到MOP的最佳均衡点。
In the same time, the article also improved the target capture arithmetic through introducing a kind of fast image correlation matching arithmetic based on the evolutionary algorithms.
同时改进了目标识别算法，提出一种基于遗传算法的快速图像相关匹配算法。
Therefore, the evolutionary algorithms have been successfully applied to various fields, especially to some complex, large scale, nonlinear and non-differentiable optimization problems.
其独特的性能已在众多领域内获得了成功的应用，着重用于解决复杂的、大规模的、非线性、不可微的优化问题。
Inspired by the idea of hybrid optimization algorithms, this paper proposes two hybrid Quantum Evolutionary algorithms (QEA) based on combining QEA with Particle Swarm optimization (PSO).
文章将量子进化算法(QEA)和粒子群算法(PSO)互相结合，提出了两种混合量子进化算法。
Inspired by the idea of hybrid optimization algorithms, this paper proposes two hybrid Quantum Evolutionary algorithms (QEA) based on combining QEA with Particle Swarm optimization (PSO).
文章将量子进化算法(QEA)和粒子群算法(PSO)互相结合，提出了两种混合量子进化算法。
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