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81.
Arnold Neumaier 《Journal of Global Optimization》2003,25(2):175-181
A family of multivariate rational functions is constructed. It has strong local minimizers with prescribed function values at prescribed positions. While there might be additional local minima, such minima cannot be global. A second family of multivariate rational functions is given, having prescribed global minimizers and prescribed interpolating data. 相似文献
82.
不等式组与变分不等式的极大熵函数方法 总被引:1,自引:1,他引:0
利用极大熵函数方法将不等式组及变分不等式的求解问题转化为近似可微优化问题,给出了不等式组及变分不等式问题近似解的可微优化方法,得到了不等式组和变分不等式问题的解集合的示性函数. 相似文献
83.
The system design must be started from the concept with low cost and high performance. In this point, the topological shape of the structure is very important in the view of the structural rigidities and light-weight design.In this paper, the optimization methodology is presented in the design stage of the large optical mirror. We obtain the optimal layout through the topology optimization and then design the details through the size or shape optimization for structural rigidity. 相似文献
84.
基于增广Lagrange函数的RQP方法 总被引:3,自引:0,他引:3
Recursive quadratic programming is a family of techniques developd by Bartholomew-Biggs and other authors for solving nonlinear programming problems.This paperdescribes a new method for constrained optimization which obtains its search di-rections from a quadratic programming subproblem based on the well-known aug-mented Lagrangian function.It avoids the penalty parameter to tend to infinity.We employ the Fletcher‘s exact penalty function as a merit function and the use of an approximate directional derivative of the function that avoids the need toevaluate the second order derivatives of the problem functions.We prove that thealgorithm possesses global and superlinear convergence properties.At the sametime, numerical results are reported. 相似文献
85.
Andrea Grosso Marco Locatelli Fabio Schoen 《Computational Optimization and Applications》2007,38(3):351-370
In this paper we perform a computational analysis of a population based approach for global optimization, Population Basin
Hopping (PBH), which was proven to be very efficient on very challenging global optimization problems by the authors (see
). The experimental analysis aims at understanding more deeply how the approach works and why it is successful on challenging
problems. 相似文献
86.
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
87.
文章建立一个随机内生增长模型来阐明主要政策参数对经济增长与社会福利的影响.若对生产函数、效用函数、偏好及随机干扰作一些特殊的假设,我们证明了主要政策参数的均衡值能被模型参数唯一决定.进一步我们还得到了期望增长率与储蓄的清晰解.文章的最后,我们证明了政府支出直接影响个体决策者的决策:即提高经济增长率将减少福利;反之,增加福利将减少增长率. 相似文献
88.
In this note we show that many classes of global optimization problems can be treated most satisfactorily by classical optimization theory and conventional algorithms. We focus on the class of problems involving the minimization of the product of several convex functions on a convex set which was studied recently by Kunoet al. [3]. It is shown that these problems are typical composite concave programming problems and thus can be handled elegantly by c-programming [4]–[8] and its techniques. 相似文献
89.
C. Bogani M. G. Gasparo A. Papini 《Journal of Optimization Theory and Applications》2007,134(1):47-59
We propose a pattern search method to solve a classical nonsmooth optimization problem. In a deep analogy with pattern search
methods for linear constrained optimization, the set of search directions at each iteration is defined in such a way that
it conforms to the local geometry of the set of points of nondifferentiability near the current iterate. This is crucial to
ensure convergence. The approach presented here can be extended to wider classes of nonsmooth optimization problems. Numerical
experiments seem to be encouraging.
This work was supported by M.U.R.S.T., Rome, Italy. 相似文献
90.