分派问题的灵敏度分析及其应用

讨论分派问题的效率矩阵的元素发生变化时,对最优解的影响;在保持分派问题最优解不变的情况下,效率矩阵的元素的变化范围;及当分派问题的最优解发生变化后,如何用简单的方法求得新的最优解等.     

缩小可行域求线性规划的整数最优解

新教材中添加了"简单的线性规划"一节.在求最优解的问题中,如果所求的不是整数最优解,通过平移直线的方法得出最优解,学生能够理解,也容易掌握.但如果要求整数最优解,讲解的时候利用多媒体演示学生也能理解,但在学生做作业的时候就出现了问题,学生不知从何下手.如果同样利用平移的方法,由于此时的可行域为不连续的点,很难得到最优解.这时我们可以采用缩小可行域的方法解决求整数最优解的问题.     

一类线性规划的分析解法

本文给出一类线性规划的分析解法。它同单纯形法[1]或直除法[2]相比,具有如下优点:1.不需要进行“调整”,就能直接得最优解或判定规划无解,因而计算简单。2.在得出最优解的同时就能给出全部最优解(即所有的最小值点)。     

线性规划多重最优解判别准则刍议

本构造了一些线性规划问题来探讨多重最优解的判别准则，补充了现行献中关于多重最优解判别准则描述的不足，并指出多重最优解判别准则在出现退化解时可能失效的例外情况。     

线性规划最优解集的表现

文献［１］讨论了有无穷多最优解的线性规划问题，并利用最优单纯形表格的检验数给出线性规划有无穷多最优解的判别法，本文利用最优基可行解的凸组合及最优极向的非负线性组合给出线性规划最优解集的表现，从而把线性规划最优解集的几何特征阐释清楚．     

枚举法在制定生产计划中的应用

赵学慧，赵瑛．枚举法在制定生产计划中的应用，数理统计与管理，１９９７，１６（１），１６～１８．本文通过用枚举法制定生产计划的实例，向管理人员介绍计算线性规划最优解的一种简单而易行的方法     

带随机过程的随机规划问题最优解集的过程特性与稳定性

本文证明了带随机过程的随机规划问题最优解集做为集值随机过程的可测性、可测最优解选择过程的存在性。研究了最优解集过程的平稳性、马氏性以及最优值过程的鞅性和最优解集过程的集值鞅性。最后，讨论了在有限维分布意义下最优解集过程对所含随机过程参数的连续性以及最优值过程的稳定性。     

线性分式规划问题的最优性条件

本文讨论了线性分式规划问题ｍｉｎ以及它的最优性条件．证明了它的局布最优解一定是整体最优解，并且局布最优解正定在约束条件的基本可行解处达到．     

有界变量线性规划的基线算法

本文对有界变量线性规划的算法进行了研究，得到了一种解此问题的新算法。文中根据基线算法的算法原理，通过对BL表的旋转，在各变量满足界约束的条件下，使目标函数值不断增大，直至得到有界硬上界，从而得到问题的最优解。文中给出了有界变量线性规划基线算法的计算步骤，并给出了一个例子。与单纯形法相比，采用基线算法解有界变量线性规划操作更简单。迭代次数少，解题速度更快。     

非线性不适定问题的Tikhonov正则化的参数选取方法

在Ｔｉｋｈｏｎｏｖ正则化中，如何选取正则参数极为重要，直至现在，仍有许多问题期待解决．本文对非线性不适定问题考虑了Ｔｉｋｈｏｎｏｖ正则化，提出了一个新的简单的正则参数的最优选取法，并对由此得到的正则参数，研究了Ｔｉｋｈｏｎｏｖ正则化解的收敛性，并且当ｘ－最小范数解满足“源条件”时，在适当的条件下，导出了最优收敛率．     

A nonisolated optimal solution for special reverse convex programming problems

In this paper, an efficient algorithm is proposed for globally solving special reverse convex programming problems with more than one reverse convex constraints. The proposed algorithm provides a nonisolated global optimal solution which is also stable under small perturbations of the constraints, and it turns out that such an optimal solution is adequately guaranteed to be feasible and to be close to the actual optimal solution. Convergence of the algorithm is shown and the numerical experiment is given to illustrate the feasibility of the presented algorithm.     

Two new algorithms for solving optimization problems with one linear objective function and finitely many constraints of fuzzy relation inequalities

This paper studies the optimization model of a linear objective function subject to a system of fuzzy relation inequalities (FRI) with the max-Einstein composition operator. If its feasible domain is non-empty, then we show that its feasible solution set is completely determined by a maximum solution and a finite number of minimal solutions. Also, an efficient algorithm is proposed to solve the model based on the structure of FRI path, the concept of partial solution, and the branch-and-bound approach. The algorithm finds an optimal solution of the model without explicitly generating all the minimal solutions. Some sufficient conditions are given that under them, some of the optimal components of the model are directly determined. Some procedures are presented to reduce the search domain of an optimal solution of the original problem based on the conditions. Then the reduced domain is decomposed (if possible) into several sub-domains with smaller dimensions that finding the components of the optimal solution in each sub-domain is very easy. In order to obtain an optimal solution of the original problem, we propose another more efficient algorithm which combines the first algorithm, these procedures, and the decomposition method. Furthermore, sufficient conditions are suggested that under them, the problem has a unique optimal solution. Also, a comparison between the recently proposed algorithm and the known ones will be made.     

An efficient algorithm for the regular W<Subscript>1</Subscript> packing of polygons in the infinite plane

This paper describes a new algorithm, PLANEPACK, which determines an optimal or near optimal solution for the W₁ packing of identical shapes in the infinite plane. Restricted to polygons for computational convenience, it is based on the no-fit polygon/configuration space obstacle approach. The algorithm was tested on a modest set of fourteen polygons (thirteen non-interlocking and one interlocking) and yielded a feasible solution for each. The solutions were optimal for four of the non-interlocking polygons and near optimal for the other nine. As expected though, the solution for the one interlocking polygon was sub-optimal and enhancements to the algorithm would be required for such cases.     

求解多项式规划的一个全局最优化算法

提出一个求解带箱子约束的一般多项式规划问题的全局最优化算法, 该算法包含两个阶段, 在第一个阶段, 利用局部最优化算法找到一个局部最优解. 在第二阶段, 利用一个在单位球上致密的向量序列, 将多元多项式转化为一元多项式, 通过求解一元多项式的根, 找到一个比当前局部最优解更好的点作为初始点, 回到第一个 阶段, 从而得到一个更好的局部最优解, 通过两个阶段的循环最终找到问题的全局最优解, 并给出了算法收敛性分析. 最后, 数值结果表明了算法是有效的.     

A robust algorithm for generalized geometric programming

Most existing methods of global optimization for generalized geometric programming (GGP) actually compute an approximate optimal solution of a linear or convex relaxation of the original problem. However, these approaches may sometimes provide an infeasible solution, or far from the true optimum. To overcome these limitations, a robust solution algorithm is proposed for global optimization of (GGP) problem. This algorithm guarantees adequately to obtain a robust optimal solution, which is feasible and close to the actual optimal solution, and is also stable under small perturbations of the constraints.     

On the Location of Supply Points to Minimize Transport Costs

An algorithm applicable to the problem of locating supply points optimally with respect to transport costs is given.Although the algorithm may fail to converge to an optimal solution, repeated application with judicious selections of alternative starting values will assure a good, if not optimal, solution.The algorithm has been tested and some sample results are included.     

一种具有非线性约束线性规划全局优化算法

本文提出了一种新的适用于处理非线性约束下线性规划问题的全局优化算法。该算法通过构造子问题来寻找优于当前局部最优解的可行解。该子问题可通过模拟退火算法来解决。通过求解一系列的子问题,当前最优解被不断地更新,最终求得全局最优解。最后,本算法应用于几个典型例题,并与罚函数法相比较,数值结果表明该算法是可行的,有效的。     

An achievement rate approach to linear programming problems with an interval objective function

In this paper, we focus on a treatment of a linear programming problem with an interval objective function. From the viewpoint of the achievement rate, a new solution concept, the maximin achievement rate solution, is proposed. Nice properties of this solution are shown: a maximin achievement rate solution is necessarily optimal when a necessarily optimal solution exists, and if not, then it is still a possibly optimal solution. An algorithm for a maximin achievement rate solution is proposed based on a relaxation procedure together with a simplex method. A numerical example is given to demonstrate the proposed solution algorithm.     

一种改进的蚁群算法及其在TSP中的应用

蚁群算法是一种求解复杂组合优化问题的新的拟生态算法,也是一种基于种群的启发式仿生进化算法,属于随机搜索算法的一种,并用于较好地解决TSP问题.然而此算法也有它自己的缺陷,如易于陷入局部优化、搜索时间长等.通过对基本蚁群算法的介绍及相关因素的分析,提出了一种改进的蚁群算法,用于解决TSPLAB问题的10个问题,并与参考文献中的F-W、NCSOM、ASOM算法进行比较,计算机仿真结果表明了改进算法的有效性.如利用改进的蚁群算法解决lin105问题,其最优解为14382.995933(已知最优解为14379),相对误差是0.0209%,计算出的最小值几乎接近于已知最优解.     

Computation of the optimal tolls on the traffic network

The present paper is devoted to the computation of optimal tolls on a traffic network that is described as fuzzy bilevel optimization problem. As a fuzzy bilevel optimization problem we consider bilinear optimization problem with crisp upper level and fuzzy lower level. An effective algorithm for computation optimal tolls for the upper level decision-maker is developed under assumption that the lower level decision-maker chooses the optimal solution as well. The algorithm is based on the membership function approach. This algorithm provides us with a global optimal solution of the fuzzy bilevel optimization problem.