974 resultados para global convergence
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In this study we present a combinatorial optimization method based on particle swarm optimization and local search algorithm on the multi-robot search system. Under this method, in order to create a balance between exploration and exploitation and guarantee the global convergence, at each iteration step if the distance between target and the robot become less than specific measure then a local search algorithm is performed. The local search encourages the particle to explore the local region beyond to reach the target in lesser search time. Experimental results obtained in a simulated environment show that biological and sociological inspiration could be useful to meet the challenges of robotic applications that can be described as optimization problems.
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This article uses topological approaches to suggest that education is becoming-topological. Analyses presented in a recent double-issue of Theory, Culture & Society are used to demonstrate the utility of topology for education. In particular, the article explains education's topological character through examining the global convergence of education policy, testing and the discursive ranking of systems, schools and individuals in the promise of reforming education through the proliferation of regimes of testing at local and global levels that constitute a new form of governance through data. In this conceptualisation of global education policy changes in the form and nature of testing combine with it the emergence of global policy network to change the nature of the local (national, regional, school and classroom) forces that operate through the ‘system’. While these forces change, they work through a discursivity that produces disciplinary effects, but in a different way. This new–old disciplinarity, or ‘database effect’, is here represented through a topological approach because of its utility for conceiving education in an increasingly networked world.
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Based on the homotopy mapping, a globally convergent method of parameter inversion for non-equilibrium convection-dispersion equations (CDEs) is developed. Moreover, in order to further improve the computational efficiency of the algorithm, a properly smooth function, which is derived from the sigmoid function, is employed to update the homotopy parameter during iteration. Numerical results show the feature of global convergence and high performance of this method. In addition, even the measurement quantities are heavily contaminated by noises, and a good solution can be found.
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求解跨音速翼型的反设计问题时,传统的梯度型方法一般均为局部收敛.为增大求解的收敛范围,依据同伦方法的思想,通过构造不动点同伦,将原问题的求解转化为其同伦函数的求解,并依据拟Sigmoid函数调整同伦参数以提高计算效率,进而构造出一种具有较高计算效率的大范围收敛反设计方法.数值算例以RAE2822翼型的表面压力分布为拟合目标,分别采用B样条方法,PARSEC方法及正交形函数方法等3种不同的参数化方法,并分别以NACA0012,OAF139及VR15翼型为初始翼型进行迭代计算.计算结果证明,该方法适用于多种参数化方法,且具有较好的计算效率,从多个不同的初始翼型出发,经较少次数迭代后,均能与目标翼型很好地拟合,是一种高效的大范围收敛方法.
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基于同伦映射的思想,改进了求解非线性反问题的梯度正则化算法.通过路径跟踪有效地拓宽了梯度正则化算法求解的收敛范围.对于正则化参数的修正,通过引入拟Sigmoid函数,提出了一种下降速率可调的连续化参数修正方法,在保证迭代稳定的条件下,得到较好的计算效率,同时保证该算法具有很好的抵抗观测噪声能力.实际算例表明,该方法收敛范围宽,计算效率高,在存在较强观测噪声的条件下也能得到很好的反演结果.
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Clustering behavior is studied in a model of integrate-and-fire oscillators with excitatory pulse coupling. When considering a population of identical oscillators, the main result is a proof of global convergence to a phase-locked clustered behavior. The robustness of this clustering behavior is then investigated in a population of nonidentical oscillators by studying the transition from total clustering to the absence of clustering as the group coherence decreases. A robust intermediate situation of partial clustering, characterized by few oscillators traveling among nearly phase-locked clusters, is of particular interest. The analysis complements earlier studies of synchronization in a closely related model. © 2008 American Institute of Physics.
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This paper proposes a design methodology to stabilize isolated relative equilibria in a model of all-to-all coupled identical particles moving in the plane at unit speed. Isolated relative equilibria correspond to either parallel motion of all particles with fixed relative spacing or to circular motion of all particles with fixed relative phases. The stabilizing feedbacks derive from Lyapunov functions that prove exponential stability and suggest almost global convergence properties. The results of the paper provide a low-order parametric family of stabilizable collectives that offer a set of primitives for the design of higher-level tasks at the group level. © 2007 IEEE.
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In this paper, we study the behavior of a network of N agents, each evolving on the circle. We propose a novel algorithm that achieves synchronization or balancing in phase models under mild connectedness assumptions on the (possibly time-varying and unidirectional) communication graphs. The global convergence analysis on the N-torus is a distinctive feature of the present work with respect to previous results that have focused on convergence in the Euclidean space. © 2006 Elsevier B.V. All rights reserved.
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为提高理性遗传算法遗传信息的完备性、算法全局收敛性以及算法的整体结构,给出了一个更一般化的理性算子和算法结构,证明了算法的全局收敛性.理论分析和在运动规划问题中的应用结果验证了理性遗传算法的有效性.
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This paper revisits work on the socio-political amplification of risk, which predicts that those living in developing countries are exposed to greater risk than residents of developed nations. This prediction contrasts with the neoliberal expectation that market driven improvements in working conditions within industrialising/developing nations will lead to global convergence of hazard exposure levels. It also contradicts the assumption of risk society theorists that there will be an ubiquitous increase in risk exposure across the globe, which will primarily affect technically more advanced countries. Reviewing qualitative evidence on the impact of structural adjustment reforms in industrialising countries, the export of waste and hazardous waste recycling to these countries and new patterns of domestic industrialisation, the paper suggests that workers in industrialising countries continue to face far greater levels of hazard exposure than those of developed countries. This view is confirmed when a data set including 105 major multi-fatality industrial disasters from 1971 to 2000 is examined. The paper concludes that there is empirical support for the predictions of socio-political amplification of risk theory, which finds clear expression in the data in a consistent pattern of significantly greater fatality rates per industrial incident in industrialising/developing countries.
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The Stochastic Diffusion Search (SDS) was developed as a solution to the best-fit search problem. Thus, as a special case it is capable of solving the transform invariant pattern recognition problem. SDS is efficient and, although inherently probabilistic, produces very reliable solutions in widely ranging search conditions. However, to date a systematic formal investigation of its properties has not been carried out. This thesis addresses this problem. The thesis reports results pertaining to the global convergence of SDS as well as characterising its time complexity. However, the main emphasis of the work, reports on the resource allocation aspect of the Stochastic Diffusion Search operations. The thesis introduces a novel model of the algorithm, generalising an Ehrenfest Urn Model from statistical physics. This approach makes it possible to obtain a thorough characterisation of the response of the algorithm in terms of the parameters describing the search conditions in case of a unique best-fit pattern in the search space. This model is further generalised in order to account for different search conditions: two solutions in the search space and search for a unique solution in a noisy search space. Also an approximate solution in the case of two alternative solutions is proposed and compared with predictions of the extended Ehrenfest Urn model. The analysis performed enabled a quantitative characterisation of the Stochastic Diffusion Search in terms of exploration and exploitation of the search space. It appeared that SDS is biased towards the latter mode of operation. This novel perspective on the Stochastic Diffusion Search lead to an investigation of extensions of the standard SDS, which would strike a different balance between these two modes of search space processing. Thus, two novel algorithms were derived from the standard Stochastic Diffusion Search, ‘context-free’ and ‘context-sensitive’ SDS, and their properties were analysed with respect to resource allocation. It appeared that they shared some of the desired features of their predecessor but also possessed some properties not present in the classic SDS. The theory developed in the thesis was illustrated throughout with carefully chosen simulations of a best-fit search for a string pattern, a simple but representative domain, enabling careful control of search conditions.
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A Nonlinear Programming algorithm that converges to second-order stationary points is introduced in this paper. The main tool is a second-order negative-curvature method for box-constrained minimization of a certain class of functions that do not possess continuous second derivatives. This method is used to define an Augmented Lagrangian algorithm of PHR (Powell-Hestenes-Rockafellar) type. Convergence proofs under weak constraint qualifications are given. Numerical examples showing that the new method converges to second-order stationary points in situations in which first-order methods fail are exhibited.
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As to many Latin american countries, the impacts of the recent economic globalization on the Brazilian economy have revealed a diversified tendency in spatial development when regional economic indicators are observed. This is due to the specificities or each region, as regard their sector structure, the availability of human resources and the degree of technological innovation undertaken by local enterprises. From a situation of regional inequalities observed in lhe socio-economic levels of development at the beginning of the eighties the dynamics of the Brazilian regional evolution has presented different speeds and intensities in the several spaees. This paper aims to evaluate the dynamics of Brazilian regional development during the 1985-95 period and the impacts over the working population and regional disparities in order to offer some elements to assist social and economic policy. For this purpose Dispersion Quotients and Dispersion lntensity Coefficients were calculated based on two variables, the Regional Gross Domestic Product anel the Working Population. The results of the analysis confirm the existence of considerable regional disparities and it was observed that thc sector and regional redistribution of the GDP indicate that in a general way, no remarkable changes occurred in the regional development in the period. The results show that although the economic policies did stimulate a global convergence process of the per capita product among regions, those policies did not attenuate economic dynamism concentration to the desired extent.
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Pós-graduação em Engenharia Elétrica - FEB
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We present two new constraint qualifications (CQs) that are weaker than the recently introduced relaxed constant positive linear dependence (RCPLD) CQ. RCPLD is based on the assumption that many subsets of the gradients of the active constraints preserve positive linear dependence locally. A major open question was to identify the exact set of gradients whose properties had to be preserved locally and that would still work as a CQ. This is done in the first new CQ, which we call the constant rank of the subspace component (CRSC) CQ. This new CQ also preserves many of the good properties of RCPLD, such as local stability and the validity of an error bound. We also introduce an even weaker CQ, called the constant positive generator (CPG), which can replace RCPLD in the analysis of the global convergence of algorithms. We close this work by extending convergence results of algorithms belonging to all the main classes of nonlinear optimization methods: sequential quadratic programming, augmented Lagrangians, interior point algorithms, and inexact restoration.