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1.
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. 相似文献
2.
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. 相似文献
3.
The filled function method is an effective approach to find a global minimizer for a general class of nonsmooth programming problems with a closed bounded domain. This paper gives a new definition for the filled function, which overcomes some drawbacks of the previous definition. It proposes a two-parameter filled function and a one-parameter filled function to improve the efficiency of numerical computation. Based on these analyses, two corresponding filled function algorithms are presented. They are global optimization methods 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. Numerical results obtained indicate the efficiency and reliability of the proposed filled function methods. 相似文献
4.
In this paper, a new global optimization approach based on the filled function method is proposed for solving box-constrained systems of nonlinear equations. We first convert the nonlinear system into an equivalent global optimization problem, and then propose a new filled function method to solve the converted global optimization problem. Several numerical examples are presented and solved by using different local minimization methods, which illustrate the efficiency of the present approach. 相似文献
5.
本文给出了一类新的求解箱约束全局整数规划问题的填充函数,并讨论了其填充性质.基于提出的填充函数,设计了一个求解带等式约束、不等式约束、及箱约束的全局整数规划问题的算法.初步的数值试验结果表明提出的算法是可行的。 相似文献
6.
Chengjun Wang Ronghua LuoKun Wu Boshun Han 《Journal of Computational and Applied Mathematics》2011,235(6):1689-1699
In this paper, we transform an unconstrained system of nonlinear equations into a special optimization problem. A new filled function is constructed by employing the special properties of the transformed optimization problem. Theoretical and numerical properties of the proposed filled function are investigated and a solution of the algorithm is proposed. Under some conditions, we can find a solution or an approximate solution to the system of nonlinear equations in finite iterations. The implementation of the algorithm on six test problems is reported with satisfactory numerical results. 相似文献
7.
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. 相似文献
8.
Weiwen Tian & Liansheng Zhang 《计算数学(英文版)》2004,22(1):69-78
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. 相似文献
9.
Filled functions for unconstrained global optimization 总被引:15,自引:0,他引:15
Zheng Xu Hong-Xuan Huang Panos M. Pardalos Cheng-Xian Xu 《Journal of Global Optimization》2001,20(1):49-65
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. 相似文献
10.
In this paper, a discrete filled function algorithm embedded with continuous approximation is proposed to solve max-cut problems. A new discrete filled function is defined for max-cut problems, and properties of the function are studied. In the process of finding an approximation to the global solution of a max-cut problem, a continuation optimization algorithm is employed to find local solutions of a continuous relaxation of the max-cut problem, and then global searches are performed by minimizing the proposed filled function. Unlike general filled function methods, characteristics of max-cut problems are used. The parameters in the proposed filled function need not to be adjusted and are exactly the same for all max-cut problems that greatly increases the efficiency of the filled function method. Numerical results and comparisons on some well known max-cut test problems show that the proposed algorithm is efficient to get approximate global solutions of max-cut problems. 相似文献
11.
The filled function method is considered as an efficient approach to solve the global optimization problems. In this paper, a new filled function method is proposed. Its main idea is as follows: a new continuously differentiable filled function with only one parameter is constructed for unconstrained global optimization when a minimizer of the objective function is found, then a minimizer of the filled function will be found in a lower basin of the objective function, thereafter, a better minimizer of the objective function will be found. The above process is repeated until the global optimal solution is found. The numerical experiments show the efficiency of the proposed filled function method. 相似文献
12.
Ai-Fan Ling Cheng-Xian Xu Feng-Min Xu 《Journal of Computational and Applied Mathematics》2008,220(1-2):643-660
A discrete filled function algorithm is proposed for approximate global solutions of max-cut problems. A new discrete filled function is defined for max-cut problems and the properties of the filled function are studied. Unlike general filled function methods, using the characteristic of max-cut problems, the parameters in proposed filled function need not be adjusted. This greatly increases the efficiency of the filled function method. By combining a procedure that randomly generates initial points for minimization of the filled function, the proposed algorithm can greatly reduce the calculation cost and be applied to large scale max-cut problems. Numerical results on different sizes and densities test problems indicate that the proposed algorithm is efficient and stable to get approximate global solutions of max-cut problems. 相似文献
13.
Discrete global descent method for discrete global optimization and nonlinear integer programming 总被引:2,自引:0,他引:2
A novel method, entitled the discrete global descent method, is developed in this paper to solve discrete global optimization
problems and nonlinear integer programming problems. This method moves from one discrete minimizer of the objective function
f to another better one at each iteration with the help of an auxiliary function, entitled the discrete global descent function.
The discrete global descent function guarantees that its discrete minimizers coincide with the better discrete minimizers
of f under some standard assumptions. This property also ensures that a better discrete minimizer of f can be found by some classical local search methods. Numerical experiments on several test problems with up to 100 integer
variables and up to 1.38 × 10104 feasible points have demonstrated the applicability and efficiency of the proposed method. 相似文献
14.
A filled function method for constrained global optimization 总被引:1,自引:0,他引:1
In this paper, a filled function method for solving constrained global optimization problems is proposed. A filled function
is proposed for escaping the current local minimizer of a constrained global optimization problem by combining the idea of
filled function in unconstrained global optimization and the idea of penalty function in constrained optimization. Then a
filled function method for obtaining a global minimizer or an approximate global minimizer of the constrained global optimization
problem is presented. Some numerical results demonstrate the efficiency of this global optimization method for solving constrained
global optimization problems. 相似文献
15.
We introduce a new Integer Linear Programming (ILP) approach for solving Integer Programming (IP) problems with bilinear objectives and linear constraints. The approach relies on a series of ILP approximations of the bilinear IP. We compare this approach with standard linearization techniques on random instances and a set of real-world product bundling problems. 相似文献
16.
In this paper, we consider the box constrained nonlinear integer programming problem. We present an auxiliary function, which has the same discrete global minimizers as the problem. The minimization of the function using a discrete local search method can escape successfully from previously converged discrete local minimizers by taking increasing values of a parameter. We propose an algorithm to find a global minimizer of the box constrained nonlinear integer programming problem. The algorithm minimizes the auxiliary function from random initial points. We prove that the algorithm can converge asymptotically with probability one. Numerical experiments on a set of test problems show that the algorithm is efficient and robust. 相似文献
17.
A class of filled functions for finding global minimizers of a function of several variables 总被引:12,自引:0,他引:12
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. 相似文献
18.
19.
We provide a complexity classification of four variants of robust integer programming when the underlying Graver basis is given. We discuss applications to robust multicommodity flows and multiway statistical table problems, and describe an effective parametrization of robust integer programming. 相似文献
20.
《Operations Research Letters》2014,42(3):226-230
We propose an Integer Linear Programming (ILP) approach for solving integer programs with bilinear objectives and linear constraints. Our approach is based on finding upper and lower bounds for the integer ensembles in the bilinear objective function, and using the bounds to obtain a tight ILP reformulation of the original problem, which can then be solved efficiently. Numerical experiments suggest that the proposed approach outperforms a latest iterative ILP approach, with notable reductions in the average solution time. 相似文献