首页 | 本学科首页   官方微博 | 高级检索  
文章检索
  按 检索   检索词:      
出版年份:   被引次数:   他引次数: 提示:输入*表示无穷大
  收费全文   42篇
  数学   42篇
  2017年   2篇
  2016年   1篇
  2014年   2篇
  2013年   4篇
  2012年   1篇
  2011年   1篇
  2010年   1篇
  2009年   2篇
  2007年   3篇
  2006年   2篇
  2004年   3篇
  2001年   3篇
  2000年   1篇
  1997年   1篇
  1996年   1篇
  1995年   1篇
  1994年   1篇
  1993年   1篇
  1992年   1篇
  1991年   4篇
  1990年   4篇
  1988年   1篇
  1986年   1篇
排序方式: 共有42条查询结果,搜索用时 109 毫秒
1.
In this paper, we present sufficient optimality conditions and duality results for a class of nonlinear fractional programming problems. Our results are based on the properties of sublinear functionals and generalized convex functions.  相似文献
2.
The global minimization of a large-scale linearly constrained concave quadratic problem is considered. The concave quadratic part of the objective function is given in terms of the nonlinear variablesx R n , while the linear part is in terms ofy R k. For large-scale problems we may havek much larger thann. The original problem is reduced to an equivalent separable problem by solving a multiple-cost-row linear program with 2n cost rows. The solution of one additional linear program gives an incumbent vertex which is a candidate for the global minimum, and also gives a bound on the relative error in the function value of this incumbent. Ana priori bound on this relative error is obtained, which is shown to be 0.25, in important cases. If the incumbent is not a satisfactory approximation to the global minimum, a guaranteed-approximate solution is obtained by solving a single liner zero–one mixed integer programming problem. This integer problem is formulated by a simple piecewise-linear underestimation of the separable problem.This research was supported by the Division of Computer Research, National Science Foundation under Research Grant DCR8405489.Dedicated to Professor George Dantzig in honor of his 70th Birthday.  相似文献
3.
We discuss a wide range of results for minimum concave-cost network flow problems, including related applications, complexity issues, and solution techniques. Applications from production and inventory planning, and transportation and communication network design are discussed. New complexity results are proved which show that this problem is NP-hard for cases with cost functions other than fixed charge. An overview of solution techniques for this problem is presented, with some new results given regarding the implementation of a particular branch-and-bound approach.  相似文献
4.
Lower bounds for the quadratic assignment problem   总被引:3,自引:0,他引:3  
We investigate the classical Gilmore-Lawler lower bound for the quadratic assignment problem. We provide evidence of the difficulty of improving the Gilmore-Lawler bound and develop new bounds by means of optimal reduction schemes. Computational results are reported indicating that the new lower bounds have advantages over previous bounds and can be used in a branch-and-bound type algorithm for the quadratic assignment problem.  相似文献
5.
6.
In this paper, we analyze various control algorithms that have been proposed for controlling spatiotemporal chaos in a globally coupled map lattice (CML) system. We reformulate the choice of feedback parameters in such systems as a constrained optimization problem and provide numerical and experimental results on the choice of optimal parameters for controlling the mean global Lyapunov exponent of a lattice. Finally, we propose a scheme to use this optimization technique to solve a learning problem in which such a CML system can be used to emulate the dynamics of an epileptic brain. This work was supported by NIH-NIBIB and CRDF grants.  相似文献
7.
A class of important problems in structural mechanics leads to optimization problems with linear objective functions and constraints consisting in (a) linear equalities and (b) inequalities imposed by the material strength, the so-called failure criteria. It is shown that a wide variety of failure criteria can be represented as systems of either second-order cone or semidefinite constraints, giving rise to respective optimization problems. Work partially supported by Air Force grants.  相似文献
8.
We introduce a novel global optimization method called Continuous GRASP (C-GRASP) which extends Feo and Resende’s greedy randomized adaptive search procedure (GRASP) from the domain of discrete optimization to that of continuous global optimization. This stochastic local search method is simple to implement, is widely applicable, and does not make use of derivative information, thus making it a well-suited approach for solving global optimization problems. We illustrate the effectiveness of the procedure on a set of standard test problems as well as two hard global optimization problems.  相似文献
9.
In this paper, we describe an algorithm for estimating the Lyapunov exponents from the chaotic dynamics of control systems. Attention is focused on optimization methods for estimating tangent maps from experimental time series data. Our numerical tests show that the algorithm is robust and quite effective, and that its performance is comparable with that of other algorithms. The properties of the algorithm are demonstrated by application to a range of data sets. We consider numerical and experimental data and discuss the computational aspects of the proposed algorithm. New feedback rules for use with optimization techniques in the stimulation of the epileptic brain are proposed. This work was supported by NIH, NSF, and CRDF grants.  相似文献
10.
In this paper, we present necessary optimality conditions for nondifferentiable minimax fractional programming problems. A new concept of generalized convexity, called (C, α, ρ, d)-convexity, is introduced. We establish also sufficient optimality conditions for nondifferentiable minimax fractional programming problems from the viewpoint of the new generalized convexity. When the sufficient conditions are utilized, the corresponding duality theorems are derived for two types of dual programs. This research was partially supported by NSF and Air Force grants  相似文献
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号