遗传算子

• Gga has been applied successfully in some optimization applications , for example knapsack problem and travelling salesman problem etc . in second chapter , we first introduce how to construct a goog - point set and the steps to solve problem . then give an example of how to arrange sports items in a track and field game to use gga in the end
  它采用数论中佳点集的方法来构造新的遗传算子，利用佳点集的性质和特点来提高算法的效率和收敛性，并且已经成功的在一些优化问题中得到了应用，例如背包、货郎担等典型的np难问题。
• According to the shortage of ga converging to a local optimal solution because of reducing the diversity of individuals , the theory of biological immune system is cited , the immune operators including calculation the densities of antibodies , activating or suppressing antibodies and making the memory cell are designed , and effectively combined with ga operators
  同时，针对遗传算法在收敛计算后期，由于种群趋向单一化，出现早熟现象而陷入局部最优解的缺点，借鉴生物原理的免疫系统，设计出抗体浓度计算、抗体的抑制/促进、构造记忆单元等多个免疫算子，并与遗传算子进行有效结合。
• This thesis contrasts and analyses the different calculation - method , and improves the genetic algorithm in the parameter inversion of the rock and soil engineering . the strategies are mainly in the following three aspects : 1 , new searching way is compositely searching genetic algorithm which is made up of the acceleration method and genetic algorithm when it partially calculates in the later time ; 2 , index function is inducted in gengetic operators , at the same time repeated select and double exchange pool are used ; 3 , splicing crossover , which reserves some new evolution factions , improves authority function accaunting the capabilities and kinds
  本文对优化算法中不同求解方法进行对比分析，针对遗传算法在岩土工程参数反演运算中进行了改进，改进的策略主要集中于三个方面： 1 、提出了在遗传算法中融入形加速法的改进方法? ?复合遗传搜索法； 2 、针对遗传算子的选择策略，引入指数适值方法，设置双交换池，提出了重复筛选法； 3 、加强对劣势种群的内部优良信息的遗传功能的改进，引入权函数，扩大可交叉算子的种类，保留各算子的进化功能，提出了融合交叉运算法。
• An optimizing method based on biological evolution - genetic algorithm is proposed to the problem of the construction process planning analysis . adapting the successful experience of path optimization problem , improved genetic operators are adopted : the sequence of numbers , which is arranged by the removal order of members , is assumed to represent a chromosome by natural code ; transforming baseline information of this problem into immune operators ; combining rank - based model with elitist model ; designing special crossover and mutation operators . the mathematical model for computer and special programs are provided in this paper
  借鉴遗传算法在求解路径优化问题上的成功经验，应用了改进的遗传算子：采用自然数对结构去除构件进行编码，将所求问题的基本信息转换成免疫算子，采用稳态最优保存策略和排序选择方法相结合进行选择，采用适用于本问题研究的特殊的交叉算子和变异算子，从而来讨论在桁架结构施工路径优化问题中使用遗传算法的可能性。
• This article studies application of genetic algorithm in virtual enterprise production planning and control system ， and discusses the methods and skills of using genetic algorithm . at last , take a concrete application example as the background , the thesis designed a frame of synergic production planning and control information system of ve
  论文对遗传算法在虚拟企业计划与控制优化中的应用进行了初步研究，针对虚拟企业生产计划和控制中的两个具体问题，设计了适合该问题的数学模型、编码方法、适应度函数和遗传算子，探讨了用遗传算法解决实际问题的方法和技巧。
• Lastly , an evolutionary algorithm is proposed for obtainment of matching domain blocks of fractal partition in image compression . it makes use of the partition iterated function system and fractal image compression . chromosome representation , initialization of population , design of special genetic operators are introduced explicitly
  最后作者提出了一种改进的用于求解具有全局最优的自相似分块匹配的演化算法，详细地讲述了染色体编码方法、适应度函数的设计、遗传算子的设计和采样机理。
• This article is divided into three part . the first chapter in - troduces research history of genetic algorithm and biological back - ground briefly at the beginning , then discuss the basic realization method of the algorithm , its operators , its basic characteristic , its applications as well as some thoughts of the author about how to use genetic algorithm to solve problems
  全文共分三章，在第一章首先简单介绍了遗传算法的研究历史，生物背景，继而简述了遗传算法的基本实现步骤和基本遗传算子的实现方案以及遗传算法的基本特点和目前的基本应用情况以及作者在应用遗传算法处理问题中的一点心得。
• Secondly , gnetic agorithm ( ga ) is applied to design the load recognising processing of structure . it can solve how to search the optimal solution in the load detecting recognising . according to the structure of basic ga , the chromosome coding and decode , fitness , and genetic operator are designed . it is validated through the experiment of load recognising in the model of wing - box
  利用光纤智能夹层来采集结构应变分布,引入遗传算法来解决识别过程求全域优化解(载荷)的问题。根据基本遗传算法的构造过程设计了染色体的编码与解码、适应度函数和遗传算子等重要步骤,并在机翼盒段试件上进行载荷识别试验验证。
• On the base of brief introduction simple theory of genetic algorithms , we discuss the value of each genetic operator and the means of genetic operation . correct scheme of genetic algorithms is given out according to the special bolted sphere node . the genetic algorithms optimal program is compiled in the environment of matlab using the method of transferring parameters among the main function and the sub - function
  为此，首先分析了螺栓节点球的球心误差，并通过矩阵变换理论给出计算球心误差的公式，进一步讨论了自动分度角度的计算方法；在简介遗传算法的基本原理的基础上，对各遗传算子的取值及遗传操作方法进行了讨论，针对典型的螺栓节点球零件给出了具体的遗传算法执行方案；通过matlab软件编程环境进行程序的编制，利用主函数和子函数之间参数传递的方法实现了遗传算法优化，并且编制了图形用户界面，对优化结果采用图文结合的形式输出。