Improved Genetic Algorithm and Its Application in TSP

Crossover operator and mutation operator are basic operators of genetic algorithm , which play important roles in improving the quality of the solution populations. We propose the improved crossover operator , mutation operator and rotation operator on the basis of good point set with the traveling salesman problem , the experimental result shows these operators are very efficient.     

改进遗传算法在饲料配方设计中的应用

针对现有饲料配方软件的局限性,以白绒山羊饲料配方为例,提出一种基于改进遗传算法的求解方法。与标准遗传算法相比,采用随机联赛选择替代轮盘赌模型,优化了选择策略;采用不同的随机数交叉和高斯变异,改进了交叉算子与变异算子。测试结果表明,该方法具有良好的运算效率,拓宽了搜索空间,提高了对重点区域的搜索能力,降低了成本,为复杂问题的优化提供了一种新的思路。     

Application of Improved Multi-population Genetic Algorithm to Damage Identification of Soil-wall System

The method of damage identification in soil-wall system was studied; a new approach based on improved multi-population genetic algorithm (IMGA) was developed. First, the simplified dynamic-detection model of soil-wall system was established, meanwhile, the theoretical analysis of characteristic equations in soil-wall system was conducted when soil in damage status. The objective function based on characteristic equations was established. Then, the improvements of multi-population genetic algorithm, including the adoption of real-valued representation, adaptive cross operator and adaptive mutation operator, were conducted. Finally, the localization and quantification of the soil-wall system damage were performed by IMGA with and without the consideration of noise, respectively. The results indicate that damage location and damage extent can be detected efficiently, and anti-noise performance is better.     

An Improved Genetic Algorithm for Optimum Design of Power Transformers

In order to enhance the ability of global searching for genetic algorithm in power transformers optimization design, some interrelated key technique problems such as encoding method, genetic operators, restrict condition, fitness function for the traditional genetic algorithm are further reformed. An Improved Genetic Algorithm (IGA) is developed. The optimal results of a representative mathematical example show that IGA has high efficiency of global searching. At the same time, a multi-objective algorithm based on IGA is studied in this paper. IGA is applied to the single and multi-objective optimum design of S9 power transformers for the first time. All the achievements in the paper are verified a practical S9-1000/10 kV power transformer. All the optimization results are satisfactory and show that IGA has powerful ability of global searching, excellent solution precision and has a bright application prospect in the fields of power transformers design.     

A Genetic Algorithm Based on Repeating Crossover and Optimum Maintaining Strategy

A novel genetic algorithm,simply written as REGA, is proposed with the idea to limit the number of repeating crossover and replacing the worst individuals of the current generation by the best ones of the former generation. The algorithm overcomes the premature phenomenon of the simple genetic algorithm. According to Markov's limitation theorem, we prove its global convergence,explore the properties of the genetic algorithm written as RSGA only based on repeating crossover,and provide a method to calculate the mathematic expectation on the absorption time for the two algorithms. Finally,the simulation shows that the algorithm REGA can solve the optimization problem containing more than one global optimal solutions,on one hand,while eliminating the drawback of local optimum and rapidly enhancing the average fitness. On the other hand, REGA is valuable for function optimization.     

Distribution Network Structure Planning Based on Improved Immune Genetic Algorithm

Distribution Network Structure planning is a complex combinatorial optimization problem,which is difficult to solve properly by using traditional optimization methods.In order to solve this problem,Improved Immune Genetic Algorithm is introduced to the distribution network optimal planning. Improved Immune Genetic Algorithm draws into the immune diversity and antibody's density mechanism to maintain the individual's diversity and remains evolution algorithm's global stochastic searching ability,so it can promote diversity and the whole optimal-searching ability of genetic algorithm.The optimal module takes the minimum annual cost as its object,and the capacity and voltage drop of feeder and the radiation of distribution network as its restrictions.According to the require of radiation of distribution network,the spanning tree of the alternative network is taken as the initial solution to speed up the calculation.And the branch-exchange method is used in designing crossover operator and mutation operator to avoid the radiation checking and enhance the optimizing ability.This algorithm has been illustrated effectively by examples,at the same time,the calculation example demonstrates that,the algorithm has higher calculation speed than the traditional immune genetic algorithm.     

Application of Improved Hierarchic Genetic Algorithm to Damage Detection of the Main Girder for Cable-stayed Bridge

In the process of damage identification for high-order nonlinear structure such as cable-stayed bridges by the standard genetic algorithm, premature convergence would appear. In order to avoid this, an improved hierarchic genetic algorithm was proposed. The cable force change was used to establish the optimization function and threetypes of standard genetic algorithm were combined with variable fine-tuning and hierarchic strategy.To establish a hierarchical genetic algorithm with catastrophe characteristics A single-tower cable-stayed bridge model was used in the numerical simulation and the result showed that the probability of premature convergence was reduced in the improved hierarchic genetic algorithm and and the cable-stayed bridge damage was identified effectively. The anti-noise performance was better.     

Improvement and Application of Immune Genetic Algorithm in Structural Damage Identification

In order to solve structural multi-damage identification problem, a two-stage method based on Bayesian theory and immune genetic algorithm (IGA) is presented. Firstly, structural modal strain energy and frequency are considered as two kinds of information sources, and Bayesian theory is utilized to integrate the two information sources and preliminarily detect structural damage locations. Then, immune genetic algorithm is used to identify structural damage extents. Considering the convergence rate of basic IGA is still not very good, some improved strategies, such as culture vaccine, two termination conditions, are presented. It is shown that the two-stage method can precisely identify structural damage locations and extent, and the calculated results of the proposed improved IGA are obviously better than those of both the basic IGA and simple genetic algorithm.     

Application of RBF Algorithm Based on Generalized Genetic Optimization in Prediction Model for Molten Iron Desulfuration

Desulfuration process is a very sophisticate reaction which is not only diverse but also non-line. A RBF algorithm based on generalized genetic optimization is proposed after studying the standard genetic and RBF algorithm. The authors also introduce its application in prediction Model for molten Iron Desulfuration. The algorithm perfectly resolve the problem of random selection of RBF cluster center number. Furthermore, it also reduces the time which GA uses. Comparison between the simulation results of RBF and RBF algorithm Based on GGA optimization further proves the efficiency and precision of its application in Prediction Model for Molten Iron Desulfuration. Finally the result of the test shows that after adopting the algorithm, the end-point hitting ratio can reach eighty-five percent. This indicate the algorithm has the engineering practicability.     

Dynamic Route Guidance System Based on Genetic Algorithm

The study on Dynamic Route Guidance System (DRGS) is an important research in the field of Intelligent Transportation System(ITS),which guide the behaviors of travelers by providing them with optimal route based on real-time traffic information. As a result the travel time can be saved and the traffic congestion can be avoided. The route guidance algorithm can compute the best route between the begin point and destination. The globe near best property and real-time property must be considered , the Genetic Algorithm have qualifications for globe optimal and parallel algorithm. Genetic algorithm(GA),for solving the shortest route,is proposed in this thesis?The ordered real code rule,crossover,mutation are given. The efficiency of the GA is proved through an example.     

Material Recombined System Based on Genetic Algorithm

A new and better mathematical model is presented, which is based on the in-depth analysis of the material recombined system and the sufficient expenses produced during the material recombined. In order to solve the problem, the authors choose the genetic algorithm, put forward a improved coding method, and get satisfactory answer through experiments. Advantages of efficiency and economic value are given.     

遗传算法优化人工神经网络模型在日光温室湿度预报中的应用

提出一种基于遗传算法优化BP神经网络的方法预测日光温室湿度环境因子。实测日光温室内影响空气湿度的环境因子组成数据样本作为神经网络的输入,采用基于实数编码的遗传算法替代随机设定神经网络的初始权阈值,然后通过改进的BP算法在由遗传算法确定的搜索空间中对网络进行精确训练。模型预报值和实测值基于1：1线的决定系数R2和预测平均相对误差MSE分别为0.9857和3．1％。结果表明,遗传算法优化BP神经网络预报模型收敛速度快、预测精度高。可为日光温室的湿度环境调控制提供理论依据和决策支持。     

Research of Sensitivity Genetic Algorithm for Inverse Computation of Structure

The sensitivity genetic algorithm is developed in order to carry out effectively the inversion analysis of the diagnosis of the structure damage. The genetic algorithm with the technique of sensitivity can not only reduce the operation time of the program     

Learning Causality Diagram Structure Based on Genetic Algorithm

The Causality Diagram theory,which adopted graphical expression of knowledge and direct causality intensity of causality,overcomes some shortages in Belief Network and has evolved into a mixed causality diagram methodology coped with discrete and continuous variable.But it is difficult that the structure of Causality Diagram given by expert.Because the complexity of causality diagram structure goes up exponentially through the number of the vertex's increasing,it is NP-hard problem to find the most possible structure from a set of data.The authors discuss approaches and present Genetic Algorithm,to find the most possible structure from a set of data.Experiment shows the method is effective.     

棉花遗传连锁图谱及其应用研究进展

 基于DNA标记的遗传连锁图谱, 是研究植物基因组结构、功能以及进化的重要工具。随着分子标记技术的发明和应用,RFLP,RAPD,AFLP,SSR等多种DNA标记技术被用于棉花遗传连锁图谱的构建以及棉花重要农艺性状基因的定位。本文通过对现有异源四倍体棉种的遗传图谱的分析,发现异源四倍体棉花种间遗传图谱已相对饱和,但所构建陆地棉种内遗传连锁图的基因组覆盖率低;同时QTL定位研究较多,MAS、图位克隆和物理图谱构建工作已经展开。今后棉花遗传图谱的研究任务,一方面是增加现有种间图谱的标记密度,另一方面是构建覆盖陆地棉全基因组的遗传图谱。     

烟草N基因及其在烤烟遗传育种中的应用

N基因起源于烟草野生种粘毛烟草(Nicotiana glutinosa),属于TIR-NBS-LRR类抗病基因,介导烟草花叶病毒(tobacco mosaic virus, TMV)的抗性,通过转座子标签法得到克隆,目前,N-TMV互作是研究最早且最多的植物-病原菌互作模型之一。文章从转录产物、表达特征、温度敏感性、对应无毒基因等研究内容回顾了N基因在结构、表达、作用机理等方面的研究进展及现状,归纳了以N基因为TMV抗源在烤烟遗传育种中的应用及取得的成果,并从抗TMV机制研究、抗TMV种质鉴定、种质资源利用等方面对N基因在烤烟抗TMV育种中的高效利用提出了展望。     

Optimum Analysis of Damper Braces Based on Genetic Algorithm

The aims at optimization of structure with damper braces is studied in this paper. The sum of damping coefficient of all damper braces is considered as a goal function, and the storey displacements are considered as constraint conditions. The program,which introduces the non-proportional damp matrix, based on genetic algorithm and time history is used to analyze the optimization of a damper braced frame. The results are reasonable and show that the genetic algorithm is an efficient method to optimize the damper braced structure.     

DNA分子标记技术在烟草遗传育种中的应用

从种质资源研究、遗传图谱构建、基因定位及分子标记辅助选择等方面综述了DNA分子标记技术在烟草遗传育种中的应用,并分析了分子标记技术在烟草遗传育种研究中存在的问题及应用前景。