基于生物地理-海鸥群优化的高维结构可靠性分析

结构可靠度分析中,一阶可靠度方法由于简单高效而得到广泛使用.然而,对于高维非线性问题,一阶可靠度方法可能导致不收敛或者早熟.为克服这一缺陷,本文提出了基于生物地理-海鸥群优化的改进一阶可靠度方法.针对海鸥群优化算法在寻优过程中存在的早熟现象,引入生物地理优化算法中的变异与迁移机制,提出生物地理-海鸥群混合优化策略进行寻...     

Design of fractional-order variants of complex LMS and NLMS algorithms for adaptive channel equalization

Equalization filtering is an effective technique applied to minimize the inter-symbol interference (ISI) in multipath fading channels; the problem gets worse for higher-order constellations which are required for high data rates in today’s communication systems. The least mean square (LMS) filter is a computationally efficient and easily implementable algorithm but suffers from slow convergence; highly complex filters are required to nullify the effects of ISI. In this paper, we develop complex modified fractional-order (FO) nonlinear variants of the LMS and the NLMS algorithms and apply in adaptive channel equalization, in both feed-forward and decision feedback configurations. In addition to the standard first-order derivative, the update in the modified LMS also depends on the FO derivative of the mean square error, the final update is formed using a combination of conventional update term and a nonlinear term obtained through Riemann–Liouville fractional derivative. The step size of the FNLMS scheme in fractional part is not only a function of the input energy but also the FO. The differintegral operator working as differentiator helps improve the convergence rate because the algorithm becomes nonlinear; the fractional algorithms provide more parameters to control the rate of convergence and have simple implementation with almost similar complexity. The performances of the schemes are validated through extensive simulation results for block fading channels (frequency flat and selective) to evaluate the symbol error rate for higher-order quadrature amplitude modulation schemes, mean square error and combined channel and equalizer responses to show the improved inverse modeling of the channel. Simulation experiments confirm the superiority of the proposed algorithm over the traditional counterparts.     

基于混合遗传算法的动力系统阻尼参数识别方法

将动力系统阻尼参数识别反问题转化为非线性优化问题处理，提出了基于遗传算法的动力系统阻尼参数识别方法。为了提高简单遗传算法的计算效率和处理早熟问题，将模拟退火算法与遗传算法相结合，建立了混合遗传算法。数值计算结果表明，本文所建立的方法对于求解参数识别反问题和非线性优化问题是非常有效的，并且具有良好的鲁棒性和全局收敛能力。     

Finding attractors of continuous-time systems by parameter switching

The review presents a parameter switching algorithm and his applications which allows numerical approximation of any attractor of a class of continuous-time dynamical systems depending linearly on a real parameter. The considered classes of systems are modeled by a general initial value problem which embeds dynamical systems continuous and discontinuous with respect to the state variable, of integer, and fractional order. The numerous results, presented in several papers, are systematized here on four representative known examples representing the four classes. The analytical proof of the algorithm convergence for the systems belonging to the continuous class is presented briefly, while for the other categories of systems, the convergence is numerically verified via computational tools. The utilized numerical tools necessary to apply the algorithm are contained in Appendices A, B, C, D and E.     

采用小生境技术的混合蛙跳算法

混合蛙跳算法是一种新兴的启发式全局优化算法。本文研究了其寻优机制,提出了一种采用小生境技术的混合蛙跳算法：运用RCS小生境技术,使各子种群动态形成了互相独立的搜索空间;在解的更新公式中,设计了一种自适应因子来调节移动步长;采用种群淘汰机制,随机初始化已陷入局部最优的子种群。实验结果表明：本文给出的算法有效提高了寻优精度和收敛速度。     

基于ESGA遗传算法的水射流自驱旋转喷头优化设计

超高压水射流自驱旋转型喷头是目前广泛应用于船壁除锈的一种装置，其布局方式直接影响船壁除锈的效率和质量，目前喷头布局多依赖工程经验，缺少准确的理论分析和优化技术支持。针对水射流自驱旋转型喷头的布局优化问题，在传统遗传算法（genetic algorithm,GA）的基础上，提出一种基于“锦标赛选择”的精英策略遗传算法（elitist strategy genetic algorithm,ESGA），该算法通过采用种群进化过程中精英个体直接保留到下一代的进化策略，从而有效提高算法的全局收敛能力和算法的鲁棒性。结合旋转喷头扫掠冲击性能和轨迹特征，以喷头移动路径垂直打击面上的能量分布均匀度为衡量标准，建立超高压水射流自驱旋转型喷头的螺旋扫掠冲击离散化时间优化模型，并分别利用两种遗传算法对其进行优化改进。对一字形水射流自驱旋转型喷头的布局优化研究发现，经ESGA算法优化的旋转喷头，其扫掠冲击能量分布均匀度较原喷头布局提升了47.2%，其收敛精度也高于GA算法。经对ESGA算法优化后的喷头实验验证发现，ESGA优化方案较原设计方案除锈效率提高了42.0%。改进的ESGA优化算法可行性强，能够在收敛...     

A fractional two‐step implicit algorithm using curvilinear collected grids

An efficient fractional two‐step implicit algorithm is reported to simulate incompressible fluid flows in a boundary‐fitted curvilinear collocated grid system. Using the finite volume method, the convection terms are discretized by the high‐accuracy Roe's scheme to minimize numerical diffusion. An implicitness coefficient Π is introduced to accelerate the rate of convergence. It is demonstrated that the proposed algorithm links the fractional step method to the pressure correction procedure, and the SIMPLEC method could be considered as a special case of the fractional two‐step implicit algorithm (when Π=1). The proposed algorithm is applicable to unsteady flows and steady flows. Three benchmark two‐dimensional laminar flows are tested to evaluate the performance of the proposed algorithm. Performance is measured by sensitivity analyses of the efficiency, accuracy, grid density, grid skewness and Reynolds number on the solutions. Results show that the model is efficient and robust. Copyright © 2006 John Wiley & Sons, Ltd.     

A new method of integer linear programming—Branch direction search method

An endeavour is made in this paper to present a new and simple ILP algorithm for optimization. It has the most desirable features of robustness and fast convergence. The algorithm is successful in applying it to some problems arisen in engineering design.     

A NEW METHOD OF INTEGER LINEAR PROGRAMMING—BRANCH DIRECTION SEARCH METHOD

An endeavour is made in this paper to present a new and simple ILP algorithm foroptimization.It has the most desirable features of robustness and fast convergence.Thealgorithm is successful in applying it to some problems arisen in engineering design.     

Fruit fly optimization algorithm based fractional order fuzzy-PID controller for electronic throttle

By adding an electronic throttle and a torque sensor to an engine, it is potentially possible to improve emissions and fuel economy while preserving the torque response of a conventional engine. To do so effectively, however, requires the use of proper control strategy for electronic throttle. In this paper, a kind of fractional order fuzzy PID controller is proposed and it is applied to an electronic throttle. An efficient way to tune fractional order fuzzy PID controller parameters is proposed using a fruit fly optimization algorithm (FOA), which treats the controller parameters tuning as an optimization problem with a proper fitness function. The obtained simulation results show the effective performance of the proposed method.     

优化迭代步长的两种改进增量谐波平衡法

增量谐波平衡法(IHB法)是一个半解析半数值的方法, 其最大优点是适合于强非线性系统振动的高精度求解. 然而, IHB法与其他数值方法一样, 也存在如何选择初值的问题, 如初值选择不当, 会存在不收敛的情况. 针对这一问题, 本文提出了两种基于优化算法的IHB法: 一是结合回溯线搜索优化算法(BLS)的改进IHB法(GIHB1), 用来调节IHB法的迭代步长, 使得步长逐渐减小满足收敛条件; 二是引入狗腿算法的思想并结合BLS算法的改进IHB法(GIHB2), 在牛顿-拉弗森(Newton-Raphson)迭代中引入负梯度方向, 并在狗腿算法中引入2个参数来调节BSL搜索方式用于调节迭代的方式, 使迭代方向沿着较快的下降方向, 从而减少迭代的步数, 提升收敛的速度. 最后, 给出的两个算例表明两种改进IHB法在解决初值问题上的有效性.      

基于改进粒子群算法的翼型多目标优化研究

在多目标优化研究中,为改善多目标粒子群算法的局部搜索能力,以标准粒子群算法为基础,引入单点模拟退火算法,局部进化最优个体,采用基于目标向量的共享函数法评价适应值.标准测试函数优化实例表明:本文算法比标准粒子群算法具有更好的收敛稳定性和收敛速度,收敛速度提高了近50%;针对某翼型的气动优化设计结果表明:改进算法有效缩短了优化时间,迭代代数由61减为49,调用CFD由4880减为4250次;阻力系数、升力系数、低头力矩系数分别改进了9.23%、0.42%、16.4%,取得了较好的优化效果.     

面向工程全局优化的混沌优化算法研究进展Research advances of chaos optimization algorithms for engineering global optimization

近年来,基于混沌的初值敏感性、伪随机性、遍历性以及自相似分形等非线性动力学特性所发展的混沌优化方法,是一种有潜力的工程全局优化新工具,已广泛应用于科学与工程技术的各学科领域。根据混沌优化方法的发展历程,以算法基本思想和工程应用研究状况为重点,评述了混沌神经网络优化方法、第一类混合混沌优化算法（基于混沌搜索）、第二类混合混沌优化算法（混沌序列代替随机序列）以及混沌分形优化四种主要混沌优化算法。混沌映射最早被引入神经网络,发展了混沌神经网络优化方法,可解决复杂的组合优化等全局优化问题。遗传算法及粒子群等启发式随机算法虽具全局搜索能力,但易出现早熟并陷入局部最优。然后,出现了混沌搜索的概念,研究者将其嵌入启发式算法建立了第一类混合混沌优化算法,可有效克服原启发式算法早熟收敛的缺点。随后,利用混沌映射产生的混沌序列代替启发式算法中的随机参数形成了第二类混合混沌优化算法。混合混沌优化算法有益于实现快速全局收敛和提高计算精度。最后,利用混沌分形特性,从分形理论出发提出一类新颖的混沌分形优化算法,可搜索到优化问题的所有全局最优解。此外,对混沌优化算法研究的几个发展方向进行了展望,诸如加强混沌优化算法的参数设计、处理大规模优化、多目标优化问题以及使用代理模型等。     

分数算子描述的黏弹性体力学问题数值方法

讨论由黎曼-刘维尔 (Riemann-Liouville)分数导数描述的黏弹性体力学问题的数 值方法. 该方法利用黎曼-刘维尔分数 导数定义中核函数的特性，并结合被积函数在单步中的逼近以及Newmark型数值法，建立 了分数导数计算公式. 算例表明，该算法具有收敛快、精度高、稳定性好和易于 应用和改进的优点. 在对动态系统的瞬态响应分析和有限元分析格式中，算法都获得了 满意的结果.     

An optimization method based on the generalized polynomials for nonlinear variable-order time fractional diffusion-wave equation

In this paper, an optimization method based on a new class of basis functions, namely generalized polynomials (GPs), is proposed for nonlinear variable-order time fractional diffusion-wave equation. Variable-order time fractional derivative is expressed in the Caputo sense. In the proposed method, solution of the problem under consideration is expanded in terms of GPs with unknown free coefficients and control parameters. In this way, some new operational matrices of the ordinary and fractional derivatives are derived for these basis functions. The residual function and its 2-norm are employed for converting the problem under study to an optimization one and then choosing the unknown free coefficients and control parameters optimally. As a useful result, the necessary conditions of optimality are derived as a system of nonlinear algebraic equations with unknown free coefficients and control parameters. The validity and effectiveness of the method are demonstrated by solving some numerical examples. The results demonstrate that the proposed method is a powerful algorithm with good accuracy for solving such kind of problems.     

A LEVEL-VALUE ESTIMATION METHOD FOR SOLVING GLOBAL OPTIMIZATION

A level-value estimation method was illustrated for solving the constrained global optimization problem. The equivalence between the root of a modified variance equation and the optimal value of the original optimization problem is shown. An alternate algorithm based on the Newton's method is presented and the convergence of its implementable approach is proved. Preliminary numerical results indicate that the method is effective.     

基于拟满应力设计和遗传算法的网架截面优化方法

通过在遗传算法中嵌入拟满应力算子,提出了一种以网架结构杆件截面作为离散变量的优化设计方法,即基于拟满应力设计和遗传算法的网架截面优化方法.分析结果表明,该法能够提高遗传算法的搜索效率和获得全局最优解的可靠性,对于同时有应力和位移约束的网架等空间结构截面优化问题,这种混合算法有较高的效率.     

The Boubaker polynomials and their application to solve fractional optimal control problems

In this paper, we focus on Boubaker polynomials in fractional calculus area and obtain the operational matrix of Caputo fractional derivative and the operational matrix of the Riemann–Liouville fractional integration for the first time. Also, a general formulation for the operational matrix of multiplication of these polynomials has been achieved to solve the nonlinear problems. Then, these matrices are applied to solve fractional optimal control problems directly. In fact, the functions of the problem are approximated by Boubaker polynomials with unknown coefficients in the constraint equations, performance index and conditions. Thus, a fractional optimal control problem converts to an optimization problem, which can then be solved easily. Convergence of the algorithm is proved. Numerical results are given for several test examples to demonstrate the applicability and efficiency of the method.     

Retrieval of aerosol size distribution using improved quantum-behaved particle swarm optimization on spectral extinction measurements

An improved quantum-behaved particle swarm optimization (IQPSO) algorithm is employed to determine aerosol size distribution (ASD). The direct problem is solved using the anomalous diffraction approximation and Lambert–Beer's Law. Compared with the standard particle swarm optimization algorithm, the stochastic particle size optimization algorithm and the original QPSO, our IQPSO has faster convergence speed and higher accuracy within a smaller number of generations. Optimization parameters for the IQPSO were also evaluated; we recommend using four measurement wavelengths and 50 particles. Size distributions of various aerosol types were estimated using the IQPSO under dependent and independent models. Finally, experimental ASDs at different locations in Harbin were recovered using the IQPSO. All our results confirm that the IQPSO algorithm is an effective and reliable technique for estimating ASD.     

An iterative stabilized fractional step algorithm for numerical solution of incompressible N–S equations

Stabilized fractional step algorithm has been widely employed for numerical solution of incompressible Navier–Stokes equations. However, smaller time step sizes are required to use for existing explicit and semi‐implicit versions of the algorithm due to their fully or partially explicit nature particularly for highly viscous flow problems. The purpose of this paper is to present two modified versions of the fractional step algorithm using characteristic based split and Taylor–Galerkin like based split. The proposed modified versions of the algorithm are based on introducing an iterative procedure into the algorithm and allow much larger time step sizes than those required to the preceding ones. A numerical study of stability at acceptable convergence rate and accuracy as well as capability in circumventing the restriction imposed by the LBB condition for the proposed iterative versions of the algorithm is carried out with the plane Poisseuille flow problem under different Reynolds numbers ranging from low to high viscosities. Numerical experiments in the plane Poisseuille flow and the lid‐driven cavity flow problems demonstrate the improved performance of the proposed versions of the algorithm, which are further applied to numerical simulation of the polymer injection moulding process. Copyright © 2005 John Wiley & Sons, Ltd.