Filled functions for unconstrained global optimization

The paper is concerned with the filled functions for global optimization of a continuous function of several variables. More general forms of filled functions are presented for smooth and nonsmooth optimizations. These functions have either two adjustable parameters or one adjustable parameter. Conditions on functions and on the values of parameters are given so that the constructed functions are desired filled functions.     

一类无约束离散Minimax问题的区间调节熵算法

In this paper,a class of unconstrained discrete minimax problems is described,in which the objective functions are in C^1. The paper deals with this problem by means of taking the place of maximum-entropy function with adjustable entropy function. By constructing an interval extension of adjustable entropy function and some region deletion test rules, a new interval algorithm is presented. The relevant properties are proven, The minimax value and the localization of the minimax points of the problem can be obtained by this method. This method can overcome the flow problem in the maximum-entropy algorithm. Both theoretical and numerical results show that the method is reliable and efficient.     

THE AVERAGE ABUNDANCE FUNCTION WITH MUTATION OF THE MULTI-PLAYER SNOWDRIFT EVOLUTIONARY GAME MODEL

This article explores the characteristics of the average abundance function with mutation on the basis of the multi-player snowdrift evolutionary game model by analytical analysis and numerical simulation.The specific field of this research concerns the approximate expressions of the average abundance function with mutation on the basis of different levels of selection intensity and an analysis of the results of numerical simulation on the basis of the intuitive expression of the average abundance function.In addition,the biological background of this research lies in research on the effects of mutation,which is regarded as a biological concept and a disturbance to game behavior on the average abundance function.The mutation will make the evolutionary result get closer to the neutral drift state.It can be deduced that this affection is not only related to mutation,but also related to selection intensity and the gap between payoff and aspiration level.The main research findings contain four aspects.First,we have deduced the concrete expression of the expected payoff function.The asymptotic property and change trend of the expected payoff function has been basically obtained.In addition,the intuitive expression of the average abundance function with mutation has been obtained by taking the detailed balance condition as the point of penetration.It can be deduced that the effect of mutation is to make the average abundance function get close to 1/2.In addition,this affection is related to selection intensity and the gap.Secondly,the first-order Taylor expansion of the average abundance function has been deduced for when selection intensity is sufficiently small.The expression of the average abundance function with mutation can be simplified from a composite function to a linear function because of this Taylor expansion.This finding will play a significant role when analyzing the results of the numerical simulation.Thirdly,we have obtained the approximate expressions of the average abundance function corresponding to small and large selection intensity.The significance of the above approximate analysis lies in that we have grasped the basic characteristics of the effect of mutation.The effect is slight and can be neglected when mutation is very small.In addition,the effect begins to increase when mutation rises,and this effect will become more remarkable with the increase of selection intensity.Fourthly,we have explored the influences of parameters on the average abundance function with mutation through numerical simulation.In addition,the corresponding results have been explained on the basis of the expected payoff function.It can be deduced that the influences of parameters on the average abundance function with mutation will be slim when selection intensity is small.Moreover,the corresponding explanation is related to the first-order Taylor expansion.Furthermore,the influences will become notable when selection intensity is large.     

Performance Analysis for Mobile Ad Hoc Network in Random Graph Models with Spatial Reuse

In this paper,we present a random graph model with spatial reuse for a mobile ad hoc network(MANET) based on the dynamic source routing protocol.Many important performance parameters of theMANET are obtained,such as the average flooding distance (AFD),the probability generating function of theflooding distance,and the probability of a flooding route to be symmetric.Compared with the random graphmodel without spatial reuse,this model is much more effective because it has a smaller value of AFD and alarger probability for finding a symmetric valid route.     

Some Characterizations of the Properties ■~∞ and LB_∞

The aim of this paper is to give some properties of the linear topological invariant .Using these results we show that a nuclear Fréchet space F has the property LB_∞ if and only if everyseparately holomorphic function on an open subset U×V of E×F~* has a local Dirichlet representation,where E is a nuclear Fréchet space with the property ~∞ having a basis.     

Design of a new dynamical core for global atmospheric models based on some efficient numerical methods

A careful study on the integral properties of the primitive hydrostatic balance equations for baroclinic atmosphere is carried out, and a new scheme to design the global adiabatic model of atmospheric dynamics is presented. This scheme includes a method of weighted equal-area mesh and a fully discrete finite difference method with quadratic and linear conservations for solving the primitive equation system. Using this scheme, we established a new dynamical core with adjustable high resolution acceptable to the available     

Properties of positive solutions to a nonlinear parabolic problem

This paper deals with the properties of positive solutions to a quasilinear parabolic equation with the nonlinear absorption and the boundary flux. The necessary and sufficient conditions on the global existence of solutions are described in terms of different parameters appearing in this problem. Moreover, by a result of Chasseign and Vazquez and the comparison principle, we deduce that the blow-up occurs only on the boundary (?)Ω. In addition, for a bounded Lipschitz domainΩ, we establish the blow-up rate estimates for the positive solution to this problem with a= 0.     

Statistical Inference for Partially Linear Regression Models with Measurement Errors

In this paper,the authors investigate three aspects of statistical inference for the partially linear regression models where some covariates are measured with errors.Firstly, a bandwidth selection procedure is proposed,which is a combination of the differencebased technique and GCV method.Secondly,a goodness-of-fit test procedure is proposed, which is an extension of the generalized likelihood technique.Thirdly,a variable selection procedure for the parametric part is provided based on the nonconcave penalization and corrected profile least squares.Same as＂Variable selection via nonconcave penalized likelihood and its oracle properties＂（J.Amer.Statist.Assoc.,96,2001,1348-1360）,it is shown that the resulting estimator has an oracle property with a proper choice of regularization parameters and penalty function.Simulation studies are conducted to illustrate the finite sample performances of the proposed procedures.     

Ⅱ型区间删失数据下广义部分线性模型的筛极大似然估计(英文)

This article concerded with a semiparametric generalized partial linear model （GPLM） with the type Ⅱ censored data. A sieve maximum likelihood estimator （MLE） is proposed to estimate the parameter component, allowing exploration of the nonlinear relationship between a certain covariate and the response function. Asymptotic properties of the proposed sieve MLEs are discussed. Under some mild conditions, the estimators are shown to be strongly consistent. Moreover, the estimators of the unknown parameters are asymptotically normal and efficient, and the estimator of the nonparametric function has an optimal convergence rate.     

Dynamical Properties of Morphisms on Higher Dimensional Projective Space over Local Field北大核心CSCD

Let Cv be an algebraically closed non-archimedean field, complete with respect to a valuation v. Let ϕ : PN → PN be a morphism of degree greater than one defined over Cv, Φ a lift of ϕ. Let GΦ be the Green function of Φ and ρ the chordal metric on PN(Cv). In this paper, we first study the properties of reduction of points in high dimensional projective space and reduction of automorphisms of PN with degree one. With the help of Green function GΦ of Φ, we introduce the arithmetic distance of morphisms and investigate its property. The necessary and sufficient condition which Φ has good reduction is obtained in this paper. We also describe explicitly the Filled Julia set of Φ by its Green function. © 2022 Chinese Academy of Sciences. All rights reserved.     

一个新的非线性整数规划问题的单参数填充函数算法

非线性整数规划问题是一类复杂的优化问题,填充函数算法是求解整数规划问题的一类有效方法.构造一个新的单参数填充函数,分析并证明了其填充性质;然后,基于该填充函数并结合离散最速下降法提出了一种新的填充函数算法;最后,采用新算法对6个测试函数进行数值实验,结果表明该算法具有良好的计算效果,是有效可行的.     

A parameter free filled function for unconstrained global optimization

The filled function method is considered as an efficient method to find the global minimum of multidimensional functions. A number of filled functions were proposed recently, most of which have one or two adjustable parameters. However, there is no efficient criterion to choose the parameter appropriately. In this paper, we propose a filled function without parameter. And this function includes neither exponential terms nor logarithmic terms so it is superior to the traditional ones. Theories of the filled function are investigated. And an algorithm which does not compute gradients during minimizing the filled function is presented. Moreover, the numerical experiments demonstrate the efficiency of the proposed filled function.     

Filled functions for unconstrained global optimization

This paper is concerned with filled function techniques for unconstrained global minimization of a continuous function of several variables. More general forms of filled functions are presented for smooth and non-smooth optimization problems. These functions have either one or two adjustable parameters. Conditions on functions and on the values of parameters are given so that the constructed functions have the desired properties of filled functions.     

A new filled function method for unconstrained global optimization

In this paper, a new filled function which has better properties is proposed for identifying a global minimum point for a general class of nonlinear programming problems within a closed bounded domain. An algorithm for unconstrained global optimization is developed from the new filled function. Theoretical and numerical properties of the proposed filled function are investigated. The implementation of the algorithm on seven test problems is reported with satisfactory numerical results.     

全局优化问题的一个新的无参数填充函数

求全局最优化问题的填充函数算法被提出以来,参数的选取和调整一直是制约算法有效性的因素.如何在实际的计算过程中选取合适的参数,直接影响和决定了运算速度和效率.因此,构造不含参数的填充函数就显得极为重要.提出一个新的无参数的填充函数,对其理论性质进行了分析,并给出相应的填充函数算法,数值计算验证了算法的有效性.     

求一类非光滑规划全局极小点的改进的填充函数法

考虑优化问题minx∈ΩF(x) ,针对F(x)为局部Lipschitz函数 ,本文引入了求解该优化问题的一类改进的单参数填充函数 ,给出了相应的算法和收敛估计 ,理论分析和数值结果表明该方法是行之有效的     

A new discrete filled function algorithm for discrete global optimization

A definition of the discrete filled function is given in this paper. Based on the definition, a discrete filled function is proposed. Theoretical properties of the proposed discrete filled function are investigated, and an algorithm for discrete global optimization is developed from the new discrete filled function. The implementation of the algorithms on several test problems is reported with satisfactory numerical results.     

一个无参数的填充函数算法

自从1990年Ge R.P.教授在文章【A Filled Function Method for Finding a Global Minimizer of a Function of Several Variables[J].Math.Programming,1990,46:191-204】中提出了求全局最优化的填充函数算法以来,此类算法的有效性一直受到调整参数的困扰,在上述文章最后他也期待出现无参数的填充函数.作为一种尝试,本文提出了一种新的无参数的填充函数,并在此基础上,构造出一个无参数填充函数算法.数值试验证明该算法是有效的,同时与已有的填充函数算法比较具有计算量小的优势.     

A filled function method for finding a global minimizer of a function of several variables

The concept of a filled function is introduced. We construct a particular filled function and analyze its properties. An algorithm for global minimization is generated based on the concept and properties of the filled function. Some typical examples with 1 to 10 variables are tested and computational results show that in most cases this algorithm works better than the tunneling algorithm. The advantages and disadvantages are analyzed and further research directions are discussed.