量遗传算法及其在无约束优化问题中的应用

量子遗传算法（QGA）是量子计算和遗传算法相结合的产物，将量子的态矢量表示引入到遗传算法中，具有比遗传算法更好的搜索效率和收敛性。本文首先介绍了量子遗传算法的基本原理，讨论了基于量子遗传算法的一系列改进，然后将量子遗传算法应用于无约束优化问题，实例计算表明了算法在该类问题中的有效性和可行性。     

遗传算法与组合优化问题研究

介绍了遗传算法的原理、遗传算法的求解步骤，组合优化问题的数学模型及其用遗传算法解决此类问题的一般方法，并以一单目标数学规划问题为实例来说明遗传算法在解决组合优化问题时的有效性和优越性。最后，对遗传算法存在的问题及研究趋势进行了说明。     

进化计算算法在路径优化中的应用

笔者主要想要研究优化领域中和路径优化相关的问题。在研究路径优化问题时,主要运用的优化算法是遗传算法。该算法在进化计算中,是应用范围最广的,和其他的算法相比,遗传算法更有优势。笔者针对遗传算法存在的问题对遗传算法进行了修改,提出了一些优化遗传算法的建议,并在实际运用中证明了通过优化,遗传算法可以更好的解决优化路径问题。     

Agent协商优化问题的快速混沌遗传算法

随着Internet的日益完善和电子商务的普及，如何快速、高效地进行Agent协商是我们必须面对和解决的一个重要问题。文章在Bazaar协商模型下，给出了一种快速混沌遗传算法，该算法首先将混沌机制引入遗传算法，并在搜索中，以具有一定保证的当前最优解为中心不断压缩优化变量的搜索区间，对算法进行加速。这样即克服了遗传算法过早收敛的缺点，又解决了引入混沌后遗传算法收敛慢的问题。仿真实验表明，它是解决Agent协商优化问题的一种快速有效算法。     

实数交叉算子的选取和算法改进

在总结分析实数遗传算法的基础上，根据算法搜索效果，将区域划分与转移思想应用到算法结构改进中，对复杂函数全局解搜索的实验表明，新算法在寻找复杂问题的全局解、提高搜索精度方面比基本实数遗传算法有较大改进。文中还将改进的实数遗传算法用于测量数据的估计中，得到了较好的线性和非线性参数估计结果。     

基于混合遗传算法的多目标问题规划

遗传算法在问题优化中的应用已有了许多研究，但对于大型多目标规划问题而言，由于其问题特性和计算量大而限制了遗传算法的应用。为探索新的问题求解方法，提出了一种基于遗传算法和梯度算法的问题优化混合算法。用梯度法每次迭代得到的结果来改进遗传算法的群体，而用遗传算法的最优个体与梯度算法的迭代解相比较，选择其中的最优点作为梯度法下一步迭代的初始点。通过保持迭代过程的最优解，加快了搜索速度，并保证收敛于全局最优解。算例表明该方法兼具遗传算法的全局搜索能力和梯度算法的局部搜索的特点，且具有良好的工程适应性。     

免疫遗传算法及认知无线电参数优化决策

根据感知的频谱环境变化及时优化并调整无线电参数是认知无线电的关键技术之一,也是一个复杂的非线性多目标优化决策问题。遗传算法是最适合优化问题的,但当遗传算法应用于优化问题时存在过早收敛问题。提出了基于遗传算法和人工免疫系统相结合的免疫遗传算法（IGA）来克服以上问题。由于在GA算法中引入了免疫系统中抗体和抗原的概念并在每一次迭代中丢弃亲和力较大的抗体,有效地防止了GA中过早收敛现象。最后,用免疫遗传算法来解决认知无线电的参数优化问题。仿真结果表明,免疫遗传算法可以迅速达到最优决策。     

基于遗传算法的平面麦克风阵列构型优化方法

在有限平面范围内使用较少的麦克风数量设计阵列构型，使得阵列具有更好的性能是声源定位系统中需解决的首要问题。文中提出了一种基于遗传算法的阵列优化方法，该方法以阵列波束方向图的主瓣宽度和旁瓣级为基础，兼顾麦克风的数量设计了遗传算法的适应度目标函数，通过改进遗传算法，使其在麦克风阵列优化的应用中得到实现。仿真结果表明，与传统的十字形和矩形平面均匀阵列相比，优化后的阵列构型在保证阵列性能的同时，可以减少麦克风的使用数量。相比于粒子群优化算法，改进遗传算法优化后的阵列具有更优异的性能。     

遗传算法在自动排课系统中的应用

排课问题是一个有约束的、多目标的组合优化问题，是一个已被证明的NP完全问题。本文旨在相关遗传算法和多目标优化理论的基础之上，结合数学分析的方法，研究了遗传算法在排课系统中的应用。     

基于遗传算法的雷达功能板备件优化模型

通过分析雷达装备的维修方式和可用度，建立了雷达装备的功能板（印制版）随机备件优化模型，结合遗传算法解优化问题的特点，将遗传算法引入到求解备件优化问题中来，有效地解决了这一复杂的备件优化问题，保证了雷达装备具有较高的可用度。     

Genetic algorithms applied to the scheduling of the hubble space telescope

A prototype system employing a genetic algorithm has been developed in order to determine if this technology can be applied to optimizing schedules of the Hubble Space Telescope. A non-standard knowledge structure is used and appropriate genetic operators have been created. Several different crossover styles (random point selection, evolving points, and smart point selection) are tested and the best GA is compared with a neural network based optimizer. The smart crossover operator produces the best results and the GA system is able to evolve complete schedules using it. The GA is not as time-efficient as the NN system and the NN solutions tend to be better. Work is proposed to create a classifier system that can draw more effectively on the knowledge that is available in the scheduling domain.     

一种综合赋形波束天线阵的组合算法

提出一种新的组合优化方法。先通过遗传算法得到一个初步的优化结果,再用直接搜索算法进行二次优化,这样既突出了遗传算法全局寻优的特点,又避免了它在接近最优解时出现的小幅度随机波动。以低副瓣平方余割波束天线阵的综合为例,在主瓣达到要求的前提下,组合算法得到的天线阵方向图副瓣比直接搜索算法和遗传算法的副瓣低4dB以上。     

A hybrid genetic approach for garment cutting in the clothing industry

A hybrid genetic approach is proposed for the cutting operation in the clothing industry. Garment cutting is a typical strip-packing problem, which is considered to be NP-complete. With a combination of genetic algorithm (GA) and a novel heuristic algorithm, "lowest-fit-left-aligned," the cutting problem is transformed into a simple permutation problem which can be effectively solved by the GA and the searching domain is greatly reduced. From the simulation results, it is demonstrated that the optimal results can be obtained in a reasonably short period of time.     

基于遗传算法图像模式匹配的收敛性研究

介绍了采用遗传算法进行图像模式匹配的程序概要设计,通过实例分析说明了影响GA收敛性的5个因素。通过研究GA收敛性揭示了图像匹配GA搜索过程的一些规律,为遗传选择策略特别是遗传算子的设计提供了参考。     

Determining the equivalent impedance boundary condition forcorrugated coatings based on the genetic algorithm

A methodology based on the genetic algorithm (GA) is proposed to determine the equivalent impedance boundary condition (IBC) for corrugated material coating structures. In this approach, rigorous solutions of the reflection coefficients at a number of incident angles are first calculated using a periodic method of moments (MoM) solver. The IBC model is used to predict the reflection coefficients at the same observation angles. The model coefficients are then optimized using the GA so that the difference between the approximated and the MoM predicted reflection coefficients is minimized. The GA proves efficient in obtaining an optimal IBC model. The resulting IBC model can be readily incorporated into an existing computational electromagnetics code to assess the performance of the corrugated coating when mounted on complex platforms     

Application of genetic algorithm in quasi-static fiber grating wavelength demodulation technology

A modified genetic algorithm (GA) has been proposed, which was used to wavelength demodulation in quasi-static fiber grating sensing system. The modification method of GA has been introduced and the relevant mathematical model has been established. The objective function and individual fitness evaluation strategy interrelated with GA are also established. The influence of population size, chromosome size, generations, crossover probability and mutation probability on the GA has been analyzed, and the optimal parameters of modified GA have been obtained. The simulations and experiments, show that the modified GA can be applied to quasi-static fiber grating sensing system, and the wavelength demodulation preci- sion is equal to or less than 3 pm.     

Pilot-based joint ML estimation of timing offset,CFO and channel for OFDMA uplink using minimum residue decomposition technique

In this paper, a uniform circular antenna array (UCAA) combining genetic algorithm (GA) or asynchronous particle swarm (APSO) for finding out global maximum of multi-objective function in indoor ultra-wideband (UWB) communication system is proposed. The algorithm is used to synthesize the radiation pattern of the directional UCAA to reduce the bit error rate (BER), to increase received energy and channel capacity in indoor UWB communication system. Using the impulse response of multipath channel, the BER of the synthesized antenna pattern on binary antipodal-pulse amplitude modulation system can be calculated. Based on topography of the antenna and the shooting and bouncing ray/image techniques, the synthesized problem can be reformulated into a multi-objective optimization problem which would be solved by the GA and APSO. Numerical results show that the fitness value and convergence speed by APSO is better than those by GA. The results also show that for multi-objective problem APSO compared to GA can reduce the BER substantially. Moreover, APSO can get better results for both line-of-sight and non line-of-sight cases.     

应用遗传算法进行阵列天线综合

该文采用了两种基于遗传算法的方法对线阵列天线进行了综合。仿真结果表明,这两种方法均能够逼近Chebyshev综合的结果。与Chebyshev法相比,具有灵活性强,不受天线工作频率限制等优点。其中第二种方法将遗传算法与Schelkunoff法结合起来,能够方便精确地在指定位置得到零点并满足其它的优化条件。     

遗传算法在FIR滤波器设计——频率抽样法中的应用

本文介绍了遗传算法在FIR滤波器设计——频率抽样法中的应用.用遗传算法确定过渡带样本值,解决了传统方法(查表法)不能保证数据是最优的问题.本文还对标准遗传算法进行了适当的改进.给出了FIR数字低通、带通滤波器设计的两个例子.实验结果说明通过遗传算法设计的FIR滤波器性能较查表法得到了改善.     

基于说话人识别的GMM/GA算法

在实时平台上,高斯混合模型(GMM)具有计算有效性和易于实现的优点。最大似然规则中,模型参数不断更新,但由于爬山特征,任意的原始模型参数估计通常将导致局部最优;遗传算法(GA)适于求解复杂组合优化问题及非线性函数优化。提出了基于说话人识别的可以解决GMM局部最优问题的GMM/GA新算法,实验结果表明,提出的GMM/GA新算法比纯粹的GMM算法能获得更优的效果。