Key technologies as the basis for calculating the evolution of intelligent algorithms, as a result of biological evolution by simulating the process of "survival of the fittest, survival of the fittest" principle in the complex and nonlinear problem solving showed good adaptability, parallelism, robustness, etc. many advantages, but as a new frontier by many experts and scholars in the field of attention. Despite the evolutionary algorithm in the bio-engineering, machine learning, adaptive, neural network, in areas such as economic forecasts has been widely used, but the application is basically a special issue-specific computing model, on the evolutionary algorithm to guide the general theory is still in exploration stage, in theory and in applications that need to be solved, there are still many problems. In this paper, a brief review and synthesis of evolutionary algorithm research at home and abroad, as well as to discuss Theory of genetic algorithms on the basis of trying to use electronic and information science, communication technology, computer science, modern mathematics, optimal control theory, statistical mechanics theory of the integrated cross-disciplinary knowledge to explore the theoretical aspects of evolutionary algorithms and applications, through discussions Theoretical aspects of evolutionary algorithm evolutionary algorithm research and hardware in the TSP, as well as the application of evolutionary algorithm to study the development of a new direction, to make up for the previous study of evolutionary algorithms lack of evolutionary algorithm for the feasibility of developing a new way.
Keywords :Evolutionary algorithm, genetic algorithm, TSP, the evolution of hardware
研究目标
(1) 用演化算法中的一种来解决生活中其它的问题。
(2) 为了提高算法的效率、改善算法的性能,人们对传统的演化算法做了诸多改进,如多种群和变种群策略、混合策略、稳态(steady state)策略等。用其中一种算法来解释改进的先进性。
（3）从遗传算法、演化策略、演化规划和遗传程序四个分支分别讲述了演化算法的基本结构及原理、步骤。
（4）从演化计算的算法设计、理论分析和应用的角度对演化计算这一新技术进行系统全面地阐述和讨论。
（5）介绍演化算法的主要分支、主要特点及演化计算的研究内容及其前景
（6）介绍了几种演化计算理论分析方法，讨论了演化算法在优化、非线性参数估计、自适应建模和神经网络系统设计等领域的应用及其并行实现。
（7）论述了演化计算中近几年兴起的一个新方向——演化硬件等内容。
摘要（本论文范文的论文综述） I
Abstract II
1.绪论 1
1.1．演化计算的主要分支 1
1.2遗传算法 1
1.3演化策略 5
1.4演化规则 5
1.5遗传程序设计 6
1.6演化计算的研究内容发展现状及前景 6
1.6.1演化计算的研究内容 6
1.6.2演化计算的发展现状 8
1.6.3演化计算的未来发展趋势 9
2演化计算的基本原理 10
2.1演化计算的主要特点 10
2.2演化算法的基本结构 11
3.演化算法的设计 12
3.1演化计算程序设计环境 12
3.2.设计演化算法的基本步骤 13
3.3编码表示 13
3.4.适应函数的确定 15
3.5.选择策略 15
3.6.遗传算子的设计 16
3.7.控制参数的选取 16
3.8.演化算法的改进 17
4.演化算法硬件化及软件实现 18
4.1演化硬件原理及实现方法 18
4.2演化算法硬件化构造 19
4.3演化算法的软件实现思路 19
4.4硬件结构设计 20
4.4.1 从软件实现抽象硬件模块 20
4.4.2硬件系统整体结构图及解释 21
5演化算法的应用-TSP问题 24
5.1TSP问题 24
5.2演化算法求解TSP问题 24
结束语 25
参考文献 26
致 谢 28
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