Swarm intelligence for mixed-variable design optimization

INTRODUCTION Most nonlinear optimization methods assumethat objective function variables are continuous.However, many practical engineering designproblems frequently encounter discrete variables aswell as continuous variables. Discrete variables areused in many ways such as the representation of theset of standard sized components, the decision onthe number of identical parts or the choice betweendifferent design options. For example, the numberof the teeth of a gear must be chosen …     

A pooled-neighbor swarm intelligence approach to optimal reactive power dispatch

INTRODUCTION The reactive power dispatch is aimed at mini- mizing the active power loss in the transmission network by allocating the reactive power generation under several security constraints. The reactive power dispatch problem has significant influence on secure and economic operation of power systems. The reac- tive power generation affects the overall generation cost via transmission loss. A procedure which allo- cates the reactive power generation so as to minimize the transmissio…     

Multiobjective extremal optimization with applications to engineering design

In this paper, we extend a novel unconstrained multiobjective optimization algorithm, so-called multiobjective extremal optimization (MOEO), to solve the constrained multiobjective optimization problems (MOPs). The proposed approach is validated by three constrained benchmark problems and successfully applied to handling three multiobjective engineering design problems reported in literature. Simulation results indicate that the proposed approach is highly competitive with three state-of-the-art multiobjective evolutionary algorithms, i.e., NSGA-II, SPEA2 and PAES. Thus MOEO can be considered a good alternative to solve constrained multiobjective optimization problems.     

一种改进的粒子群优化算法

为了克服传统粒子群算法（Pso）的早熟和局部最优问题,通过分析基于惯性权重的粒子群优化在粒子寻优过程中的可行性,提出了一种变惯性权重的改进PSo算法,并对经典的测试函数进行TN试。实验结果证明,与传统PSO算法以及基于惯性权重的PSO相比,改进算法的寻优效果较好,全局搜索能力有显著提高,并能有效地避免早熟收敛问题。     

群智能算法及其应用

群智能算法是一种新兴的演化计算技术,它已经成功地被运用于许多领域。实践证明,群智能方法是一种能够解决许多全局优化问题的有效方法。本文介绍了群智能理论的产生和发展过程,并着力阐述群智能理论中的两个主要算法（粒子群算法和蚁群算法）的算法思想以及研究现状。     

试谈结构设计优化技术在房屋结构设计

我国的建筑施工已经随着科技的进步飞速,人们对于住房的要求越来越高,在房屋在安全的基础上还要美观舒适。建筑优化设计不仅保证了建筑的美观适用,还节省了资金。现在就房屋结构优化设计的应用,讨论在实施过程中出现的实际问题和意义。     

MIS门诊挂号系统数据库设计与优化方案

依据规范化理论给出了MIS门诊挂号系统中的各数据模式详细设计过程,并据实际需求给出了库结构优化方案。结果表明,该优化方案设计合理、使用方便。     

An approach for shape optimization of stratosphere airships based on multidisciplinary design optimization

Airship shape is crucial to the design of stratosphere airships. In this paper, multidisciplinary design optimization （MDO） technology is introduced into the design of airship shape. We devise a composite objective function, based on this technology, which takes account of various factors which influence airship performance, including aerodynamics, structures, energy and weight to determine the optimal airship shape. A shape generation algorithm is proposed and appropriate mathematical models are constructed. Simulation results show that the optimized shape gives an improvement in the value of the composite objective function compared with a reference shape.     

数控玻璃加工机床横梁有限元分析及优化设计

横梁是数控玻璃加工机床关键零部件,利用ANSYS软件对其进行静、动态特性分析以及谐响应分析,获得了横梁极端工况的变形情况以及前六阶固有频率和振型,确认第2阶固有频率易引起横梁共振。以提高二阶固有频率为优化设计目标,横梁结构尺寸为优化变量,运用Isight软件及灵敏度分析方法对其进行优化。结果表明:优化后横梁质量减少了12.88kg,静变形量减少29.22kg,二阶固有频率增大13.34Hz。     

粒子群与差异演化的混合进化算法研究

将标准粒子群（PSO）算法和差异演化（DE）算法混合进行进化,把差异演化算法的优势带入到粒子群算法中,利用差异演化算法其本身具备的对粒子个体的交叉和变异操作使标准粒子群算法种群保持寻优所需的多样性．并将这种算法与标准粒子群算法、G-PSO算法等进行了对比研究,通过混合进化的方法使粒子群种群保持多样性,实验结果表明新算法避免陷入“早熟”或“停滞”的能力大大提高．     

群智能优化算法及其在生物信息学问题中的应用

生物信息学研究需要使用先进的计算工具处理大量生物的模糊的和不确定的数据。群智能优化算法以低成本、快速和准确合理地解决复杂的搜索问题的优点,使其成为一族能用以较好地解决生物信息学中的问题的启发式算法。综述群智能优化算法及其在生物信息学问题中的应用。     

构图视觉下多媒体课件优化设计探析

多媒体技术的发展极大地改变着当今教与学的方式,多媒体画面语言形式成为时下司空见惯的知识传递方式。分析多媒体课件的一般要求,结合多媒体画面语言理论和信息化传播理论,文章从构图角度系统地分析多媒体课件设计的优化过程。     

A new theoretical framework for analyzing stochastic global optimization algorithms

１　Ｉｎｔｒｏｄｕｃｔｉｏｎ　Ｓｔｏｃｈａｓｔｉｃｇｌｏｂａｌｏｐｔｉｍｉｚａｔｉｏｎａｌｇｏｒｉｔｈｍｉｓｃｏｎｃｅｒｎｅｄｗｉｔｈｕｓｉｎｇｒａｎｄｏｍｌｙｇｅｎｅｒａｔｅｄｐｏｉｎｔｓｔｏａｐｐｒｏｘｉｍａｔｅｏｐｔｉｍａｌｓｏｌｕｔｉｏｎｏｆｍａｔｈｅｍａｔｉｃａｌｐｒｏｇｒａｍｍｉｎｇ（ｓｅｅＲｅｆｓ．１～３ｆｏｒａｓｕｒｖｅｙｏｆｔｈｅｆｉｅｌｄ）．Ｆｏｒｓｏｍｅｓｔｏｃｈａｓｔｉｃｇｌｏｂａｌｏｐｔｉｍｉｚａｔｉｏｎａｌｇｏｒｉｔｈｍｓ,ｔｈｅｎｅｘｔｐｏｉｎｔｓｉｎｔｈｅｓｅｑ…     

基于混沌振荡粒子群优化的FCM文本聚类方法

针对模糊C均值聚类算法易于陷入局部极值的问题,设计了一种基于混沌振荡粒子群优化的模糊C均值聚类方法。该方法在标准PSO算法中设计了一个振荡环节并引入混沌理论以增加算法的多样性和收敛性,接着把优化后的PSO算法和模糊C均值聚类算法相结合。文本聚类的仿真实验表明,相对于PSO-FCM算法和FCM算法,CCPSO-FCM算法具有良好的全局搜索能力和收敛速度,聚类效果良好。     

基于QPSO的二级齿轮减速器的优化设计

基于量子粒子群算法理论,对二级齿轮减速器进行优化设计,并利用MATLAB软件对量子粒子群算法程序进行了设计验证。从实验结果来看,运用量子粒子群算法很好地实现了减小齿轮中心距的要求,收敛速度快,得到的结果令人较为满意。     

等离子割炬喷嘴热－流耦合分析及优化设计

等离子割炬工作原理复杂,喷嘴在冷却水温度场和流场耦合作用下工作,实物实验难度较大,文章采用CFD软件针对两种割炬喷嘴进行数值模拟,分析在不同冷却水流速度下的温度云图和温度曲线图,确定喷嘴结构,给出建议冷却水流速度。     

Adaptive multi-objective optimization based on feedback design

The problem of adaptive multi-objective optimization(AMOO) has received extensive attention due to its practical significance.An important issue in optimizing a multi-objective system is adjusting the weighting coefficients of multiple objectives so as to keep track of various conditions.In this paper,a feedback structure for AMOO is designed.Moreover,the reinforcement learning combined with hidden biasing information is applied to online tuning weighting coefficients of objective functions.Finally,the prop...     

On the developing role of physical models in engineering design education

Recent research, undertaken using participative observation methods within the Leonardo Da Vinci project ‘Open-Dynamic-Design’, provides evidence that EU industrial practice continues to value the flexibility of physical models across a range of disciplines. This research is placed within the philosophical educational framework established by Schon and examples of implementation within the Mechanical and Aerospace Engineering disciplines at the University of Glasgow are discussed. It is argued that physical models support the concurrent optimisation of design and manufacturing processes and that they represent a continuing generic tool to support engineering design education.     

Automatic relational database compression scheme design based on swarm evolution

INTRODUCTION As the Internet develops, the volume of infor- mation increases sharply. Capacity of storage me- dium increases exponentially, while the power of CPU chips increases under Moore’s Law. However, transfer bandwidth of storage medium increases much slower. For a large relational database system (with capacity between a few giga- to multi-tera-bytes), bandwidth of the magnetic disks is always the bot- tleneck of performance. In traditional database re- search, researchers stu…     

A developmental theory for Aristotelian practical intelligence

Abstract

In Aristotelian virtue theories, phronesis is foundational to being good, but to date accounts of how this particularly important virtue can emerge are sketchy. This article plumbs recent thinking in Aristotelian virtue ethics and developmental theorizing to explore how far its emergence can be understood developmentally, i.e., in terms of the growth in ordinary conditions of underlying psychological capacities, dispositions, and the like. The purpose is not to explicate Aristotle, nor to assimilate Aristotelian ideas to cognitive developmental moral theorizing, but to draw on both to build an independently plausible theory of practical intelligence and its development. It is argued that one fruitful direction attends to the psychology of virtues Aristotle associates with practical intelligence, including comprehension, understanding, sense, and cleverness, instead of Aristotle’s remarks distinguishing fully virtuous persons from the continent, incontinent and the many.