一类求解约束全局优化问题的填充函数

本文构造了一类求解约束全局优化问题的填充函数,并在适当的假设条件下, 证明了其填充性质及其它分析性质; 此外,根据所构造的填充函数设计了相应的算法, 并给出了数值试验结果, 以说明所构造填充函数方法的有效性.     

一类关于非光滑全局优化的双参数填充函数

为在有界闭集上寻找非光滑函数的全局极小点,本文在文献[12]的基础上提出了一个改进的填充函数定义,然后给出了一个新的双参数填充函数.讨论了所给填充函数的理论和数值性质并设计了相应的算法.分析表明所给填充函数对参数的选择优于相关文献中的结果.数值实验表明,本文所给出的新的填充函数算法是有效的.     

整数规划的广义填充函数算法

文[9,10]设计了直接求整数规划问题近似解的填充函数算法,但其所利用的文[2,3]的填充函数均带有参数,需要在算法过程中逐步调节。本文建立整数规划的广义填充函数的定义,说明了文[9,10]所利用的填充函数是整数规划问题的广义填充函数,并构造了一类不带参数的广义填充函数。进而本文设计了整数规划的一类不带参数的广义填充函数算法,数值试验表明算法是有效的。     

一类新的求全局优化问题的填充函数

填充函数方法是一种寻找全局极小解的有效方法.本文首先对现有的填充函数进行研究分析,然后构造出一类新的填充函数,设计算法,并通过数值试验验证了该函数和算法的有效性.     

求解带箱子集约束的非光滑全局优化问题的填充函数方法

提出了一个求解带箱子集约束的非光滑全局优化问题的填充函数方法.构造的填充函数只包含一个参数,且此参数在迭代过程中容易调节.分析了填充函数的理论性质,在此基础上设计了填充函数算法.数值计算验证了该算法的有效性.     

一个新的填充函数

填充函数法是一种解无约束全局极小化问题的方法.这种方法的关键是构造填充函数,在已发表的文献中已经介绍了几种填充函数.在此介绍只含一个参数的填充函数,并且根据此填充函数提出了一种填充函数算法.给出了用这种填充函数法解几个测试问题的计算结果.     

求总体极小值的一类填充函数

本文构造了总体极小值的一类填充函数，它是文［４］的推广，文章对所构造的填充函数的性质作了分析，并给出了一个具体的算法及数值例子。     

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.     

全局优化问题的一个单参数填充函数方法

利用改进的填充函数的定义,对一般的无约束最优化问题给出了一个新的单参数填充函数,分析并证明了此填充函数的性质.利用该填充函数,构造了新的算法,对此算法进行了数值实验,并将此算法做了比较,结果表明此填充函数算法是可行的.     

全局最优化问题的一个无参数的填充函数算法

本文研究了全局最优化问题.利用构造填充函数的方法,提出了一个新的无参数填充函数,它是目标函数的一个明确表达式.得到了一个新的无参数填充函数算法,数值试验结果表明该填充函数算法是有效的,从而推广了填充函数算法在求解全局最优化问题方面的应用.     

A class of filled functions for finding global minimizers of a function of several variables

This paper is concerned with filled function methods for finding global minimizers of a function of several variables. A class of filled functions is defined. The advantages and disadvantages of every filled function in the class are analyzed. The best one in this class is pointed out. The idea behind constructing a better filled function is given and employed to construct the class of filled functions. A method is also explored on how to locate minimizers or saddle points of a filled function through only the use of the gradient of a function.The authors are indebted to Dr. L. C. W. Dixon for stimulating discussions.     

A critical review of discrete filled function methods in solving nonlinear discrete optimization problems

Many real life problems can be modeled as nonlinear discrete optimization problems. Such problems often have multiple local minima and thus require global optimization methods. Due to high complexity of these problems, heuristic based global optimization techniques are usually required when solving large scale discrete optimization or mixed discrete optimization problems. One of the more recent global optimization tools is known as the discrete filled function method. Nine variations of the discrete filled function method in literature are identified and a review on theoretical properties of each method is given. Some of the most promising filled functions are tested on various benchmark problems. Numerical results are given for comparison.     

A New Filled Function Method with Two Parameters for Global Optimization

The filled function method is an effective approach to find the global minimizer of multi-modal functions. The conventional filled functions are often numerically unstable due to the exponential or logarithmic term and the sensitivity to parameters. In this paper, a new filled function is proposed, which is continuously differentiable, not sensitive to parameters, and not easy to cause overflow. Then a new local search algorithm is given. Based on this, a new filled function method is proposed. The simulations indicate that the proposed method is numerically stable to the variations of the initial points and the parameters. The comparison with some existing algorithms shows that the proposed method is more efficient and effective.     

An Algorithm for Finding Global Minimum of Nonlinear Integer Programming

A filled function is proposed by R.Ge[2] for finding a global minimizer of a function of several continuous variables. In [4], an approach for finding a global integer minimizer of nonlinear function using the above filled function is given. Meanwhile a major obstacle is met: if $ρ > 0$ is small, and $||x_I-\overset{*}{x}_I||$ is large, where $x_I$ - an integer point, $\overset{*}{x}_I$ - a current local integer minimizer, then the value of the filled function almost equals zero. Thus it is difficult to recognize the size of the value of the filled function and can not find the global integer minimizer of nonlinear function. In this paper, two new filled functions are proposed for finding global integer minimizer of nonlinear function, and the new filled function improves some properties of the filled function proposed by R. Ge [2].Some numerical results are given, which indicate the new filled function (4.1) to find global integer minimizer of nonlinear function is efficient.     

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.     

求解箱式约束全局优化问题的新的F-C函数（英文）

To solve the global optimization problems which have several local minimizers,a new F-C function is proposes by combining a filled function and a cross function. The properties of the F-C function are discussed and the corresponding algorithm is given in this paper. F-C function has the same local minimizers with the objective function.Therefore, the F-C function method only needs to minimize the objective function once in the first iteration. Numerical experiments are performed and the results show that the proposed method is very effective.     

A filled function method applied to nonsmooth constrained global optimization

The filled function method is an effective approach to find a global minimizer. In this paper, based on a new definition of the filled function for nonsmooth constrained programming problems, a one-parameter filled function is constructed to improve the efficiency of numerical computation. Then a corresponding algorithm is presented. It is a global optimization method which modify the objective function as a filled function, and which find a better local minimizer gradually by optimizing the filled function constructed on the minimizer previously found. Illustrative examples are provided to demonstrate the efficiency and reliability of the proposed filled function method.     

无约束全局优化的一个可调参数的填充函数

A filled function with adjustable parameters is suggested in this paper for finding a global minimum point of a general class of nonlinear programming problems with a bounded and closed domain. This function has two adjustable parameters. We will discuss the properties of the proposed filled function. Conditions on this function and on the values of parameters are given so that the constructed function has the desired properties of traditional filled function.