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1.
几何规划的序列线性方程组解法   总被引:2,自引:0,他引:2  
1 引 言 众所周知,几何规划是非线性规划中的一类特殊规划。数学规划的前辈,早已预料:若对几何规划能探索出有效可行的算法,必将把非线性规划,特别是分式规划的算法推向新的台阶,即任何非线性规划问题,在一定的条件下,都可用一串几何规划去逼近,正因为如此,近几年,我们对几何规划的理论和算法,再一次产生了浓厚的兴趣,获得了一些新的结果,写此文目的,是想引起更多的规划专家的注意和重视,把冷落了近二十年的几何规划,推向新的台阶,为非线性规划的求解开辟新的途径。 几何规划的一般形式为  相似文献   

2.
马建华  丁梅 《运筹学学报》2006,10(3):121-125
本文利用参数规划的逆问题考虑交叉规划与多目标规划的关系,把交叉规划转变为部分同变量规划组,再把部分同变量规划组转化为一个多目标规划,并说明了交叉规划的均衡解与多目标规划的最优解的关系.  相似文献   

3.
凸二次交叉规划的等价形式   总被引:1,自引:0,他引:1  
丁梅  马建华 《经济数学》2002,19(3):77-81
利用参数规划逆问题考虑凸二次交叉规划与多目标规划的关系 ,把交叉规划转变为同变量规划组 ,再把同变量规划组变为多目标规划 ,证明了凸二次交叉规划的均衡解与多目标规划的最优解的关系。  相似文献   

4.
讨论系数是模糊数的模糊正项几何规划的一种解法,利用模糊数比较方法,把系数是模糊数的正项几何规划转化为普通正项几何规划,再利用求解正项几何规划的方法有效地求解模糊正项几何规划.  相似文献   

5.
交通网络建设序列优化是交通规划中一个重要问题。文章对交通网络设计及其建设序列问题的研究现状进行了分析。按照网络建设中规划者和用户间的关系,以交通网络建设序列下的各阶段系统总费用作为上层规划,以各阶段的交通流用户平衡模型作为下层规划,建立了双层规划模型。并依照问题的特点,采用动态规划的求解方法进行探讨,而下层模型则采用了基于路径搜索的GP算法进行求解。并针对网络规划算例进行了计算,针对固定和变动客流OD两种情况下的结果进行了分析。计算的结果表明,问题的双层规划模型和动态规划求解算法能够为路网规划决策提供支持。  相似文献   

6.
一类反凸规划的全局新算法   总被引:2,自引:0,他引:2  
§1.引言 到目前为止,大多数非线性规划的有效算法都是寻求它的局部最优解,由于很难判断一个局部解是否就是一个全局解,全局规划的研究是个困难问题,反凸规划由于其可行域的非凸性甚至非连通性,目前有效算法更少。 [1]已经指出很容易把D.C.规划(即目标函数和约束函数均为二个凸函数之差)转化成为一个目标函数为线性的反凸规划:  相似文献   

7.
根据共轭函数和DC规划的性质,给出一类特殊DC规划的共轭对偶并讨论其对偶规划的特殊性质,然后利用该性质,把对这类特殊DC规划的求解转化为对一个凸规划的求解。  相似文献   

8.
本文提出了一种求解多目标模糊随机规划问题的普遍方法。这种方法在同一个理论框架内处理约束与目标中的随机性和模糊性,因此它具有相当的普遍性。确定性规划,模糊规划和随机规划都可看成是它的特例。  相似文献   

9.
以E-SV风险测度为基础提出了组合证券投资决策的效用函数,并建立了基于分式规划的投资组合选择模型,利用变换,把求解分式规划的问题转化为求解非分式规划问题。  相似文献   

10.
宿洁 《运筹与管理》2007,16(2):60-64
主要研究了非增值型凸二次双层规划的一种有效求解算法。首先利用数学规划的对偶理论,将所求双层规划转化为一个下层只有一个无约束凸二次子规划的双层规划问题.然后根据两个双层规划的最优解和最优目标值之间的关系,提出一种简单有效的算法来解决非增值型凸二次双层规划问题.并通过数值算例的计算结果说明了该算法的可行性和有效性。  相似文献   

11.
Our paper treats the primal and dual program of ?p programming. ?p programming is a generalization of ?p approximation problems. There is a strict connection between ?p programming and geometrical programming, because in both of them geometrical inequality plays a fundamental role. The structure of our paper follows that of Klafszkys [1].In the first Sections duality theorems are proved, which play an important role in mathematical programming. Most of these results can be found in Petersons and Eckers [3,4,5], but our proofs are much more simple and we show these fundamental properties more detailed.Afterwards the relation between the Lagrange function and the optimal solution pair is investigated. Regularity is investigated as well and we show the marginal value of ?p programming. In the end linear programming ?p constrained ?p approximation problems, the quadratically constrained quadratic programming and compromise programming are shown as special cases of ?p programming.  相似文献   

12.
在大量的管理决策问题中,经常会遇到目标函数的系数和右端常数为相互独立的正态随机变量的随机线性规划模型.利用对偶规划将正态随机规划化为具有α可靠度的线性规划,给出了解决该正态随机规划的一个有效方法,并对正态随机变量的参数进行了灵敏度分析,避免了由于参数估计偏差给决策带来的风险,保证了最优方案的α可靠度.  相似文献   

13.
This paper develops a wholly linear formulation of the posynomial geometric programming problem. It is shown that the primal geometric programming problem is equivalent to a semi-infinite linear program, and the dual problem is equivalent to a generalized linear program. Furthermore, the duality results that are available for the traditionally defined primal-dual pair are readily obtained from the duality theory for semi-infinite linear programs. It is also shown that two efficient algorithms (one primal based and the other dual based) for geometric programming actually operate on the semi-infinite linear program and its dual.  相似文献   

14.
Goal programming is an important technique for solving many decision/management problems. Fuzzy goal programming involves applying the fuzzy set theory to goal programming, thus allowing the model to take into account the vague aspirations of a decision-maker. Using preference-based membership functions, we can define the fuzzy problem through natural language terms or vague phenomena. In fact, decision-making involves the achievement of fuzzy goals, some of them are met and some not because these goals are subject to the function of environment/resource constraints. Thus, binary fuzzy goal programming is employed where the problem cannot be solved by conventional goal programming approaches. This paper proposes a new idea of how to program the binary fuzzy goal programming model. The binary fuzzy goal programming model can then be solved using the integer programming method. Finally, an illustrative example is included to demonstrate the correctness and usefulness of the proposed model.  相似文献   

15.
Structural redundancies in mathematical programming models are nothing uncommon and nonlinear programming problems are no exception. Over the past few decades numerous papers have been written on redundancy. Redundancy in constraints and variables are usually studied in a class of mathematical programming problems. However, main emphasis has so far been given only to linear programming problems. In this paper, an algorithm that identifies redundant objective function(s) and redundant constraint(s) simultaneously in multi-objective nonlinear stochastic fractional programming problems is provided. A solution procedure is also illustrated with numerical examples. The proposed algorithm reduces the number of nonlinear fractional objective functions and constraints in cases where redundancy exists.  相似文献   

16.
Generally, in the portfolio selection problem the Decision Maker (DM) considers simultaneously conflicting objectives such as rate of return, liquidity and risk. Multi-objective programming techniques such as goal programming (GP) and compromise programming (CP) are used to choose the portfolio best satisfying the DM’s aspirations and preferences. In this article, we assume that the parameters associated with the objectives are random and normally distributed. We propose a chance constrained compromise programming model (CCCP) as a deterministic transformation to multi-objective stochastic programming portfolio model. CCCP is based on CP and chance constrained programming (CCP) models. The proposed program is illustrated by means of a portfolio selection problem from the Tunisian stock exchange market.  相似文献   

17.
We consider maximin and minimax nonlinear mixed integer programming problems which are nonsymmetric in duality sense. Under weaker (pseudo-convex/pseudo-concave) assumptions, we show that the supremum infimum of the maximin problem is greater than or equal to the infimum supremum of the minimax problem. As a particular case, this result reduces to the weak duality theorem for minimax and symmetric dual nonlinear mixed integer programming problems. Further, this is used to generalize available results on minimax and symmetric duality in nonlinear mixed integer programming.  相似文献   

18.
Narasimhan incorporated fuzzy set theory within goal programming formulation in 1980. Since then numerous research has been carried out in this field. One of the well-known models for solving fuzzy goal programming problems was proposed by Hannan in 1981. In this paper the conventional MINMAX approach in goal programming is applied to solve fuzzy goal programming problems. It is proved that the proposed model is an extension to Hannan model that deals with unbalanced triangular linear membership functions. In addition, it is shown that the new model is equivalent to a model proposed in 1991 by Yang et al. Moreover, a weighted model of the new approach is introduced and is compared with Kim and Whang’s model presented in 1998. A numerical example is given to demonstrate the validity and strengths of the new models.  相似文献   

19.
本文讨论上层目标函数以下层子系统目标函数的最优值作为反馈的一类二层凸规划的对偶规划问题 ,在构成函数满足凸连续可微等条件的假设下 ,建立了二层凸规划的 Lagrange对偶二层规划 ,并证明了基本对偶定理 .  相似文献   

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