带有模糊容量限制的网络中的最佳最小费用量大流

本文主要讨论当网络中弧容量限制和最大流目标要求带有模糊性时的最小费最大流问题，通过构造带费用的增量网络并设法寻找其中的最佳最小费用路，给出了求解这类模糊网络流问题的算法。     

运输网络中求最小费用最大流的一个算法

给出一个求动输网络中的最小费用最大流的数值算法,证明了算法的理论依据,并举例说明算法的应用。     

无容量限制的最小费用流问题

本文研究了无容量限制的带固定费用和可变费用的单物资和二物资的最小费用流问题,并分别给出了多项式算法.最后应用该算法,计算了一个二物资的最小费用流问题的实例.     

分配网络的一个最小费用流算法

分配网络流广泛应用于解决水源、电力的调度及工厂的产品运输、分配、合成等问题.本文提出一个分配网络流的最小费用流算法.     

最小费用最大双流

本文根据一个实例建立了在容量－费用双流网络中求最小费用最大双流的模型，提出了最小费用最大双流和双流增量网络的概念，找出并证明了最小费用双流的充要条件，最后给出该模型的一个算法并估计了算杂性。     

关于有能力限制的指派问题的一点注记

首先讨论了有能力限制的不平衡指派问题的转化和最优性,并提出了采用最小费用最大流的方法求解该问题.     

遗传算法求解带容量限制的最小费用流问题

研究了带容量限制的带固定费用和可变费用的最小费用流问题,发现该问题是混合0-1整数规划问题,不存在多项式算法.在研究了最优解的结构后,结合最优解的结构特点为之设计了遗传算法,然后构造了一个100个节点的特殊网络,用计算机做了100例计算,验证了该算法具有很好的近似比和很快的收敛速度.     

网络最小覆盖流问题

网络流理论中最基本的模型是最大流及最小费用流问题. 为研 究堵塞现象, 文献中出现了最小饱和流问题, 但它是NP-难的. 研究类似的最小覆盖流问题, 即求一流, 使每一条弧的流量达到一定的额定量, 而流的值为最小. 主要结果是给出多项式时间算法, 并应用于最小饱和流问题.     

广义多品种最小费用流问题的对偶理论

基于广义多品种最小费用流问题的性质，将问题转化成一对含有内、外层问题的双水平规划，内层规划实际是单品种费用流问题，而外层问题是分离的凸规划，使用相关的凸分析理论，导出了广义多品种最小费用流问题的对偶规划，对偶定理和Kuhn-Tucker条件。     

最佳费用流

建立赋模糊数为费用权的容量－－费用网络中，据模糊决策来求解最佳费用流的网络模型，并给出这一模型的相应算法。     

Maximum flow in a network with fuzzy arc capacities

Our main concern is the maximum flow in a network in which an excess over the beforehand fixed quota of arc capacity is admissible. The problem is represented as a partially fuzzy linear programming task. A theorem equivalent to the Ford and Fulkerson one concerning the classic task of maximum flow is proved in the paper. An algorithm for searching maximum flow assuming integer values of flows on network arcs is presented.     

带模糊约束的最大流问题

首次提出带模糊约束的最大流问题，并根据网络中的弧容量限制是否带有模糊性，分别建立数学模型，给出求解这两个模型的相应算法和有关实例。     

Solving maximum fuzzy clique problem with neural networks and its applications

The maximum clique problem is an important problem in graph theory. Many real-life problems are still being mapped into this problem for their effective solutions. A natural extension of this problem that has emerged very recently in many real-life networks, is its fuzzification. The problem of finding the maximum fuzzy clique has been formalized on fuzzy graphs and subsequently addressed in this paper. It has been shown here that the problem reduces to an unconstrained quadratic 0–1 programming problem. Using a maximum neural network, along with mutation capability of genetic adaptive systems, the reduced problem has been solved. Empirical studies have been done by applying the method on stock flow graphs to identify the collusion set, which contains a group of traders performing unfair trading among themselves. Additionally, it has been applied on a gene co-expression network to find out significant gene modules and on some benchmark graphs.     

Scalarization of the fuzzy optimization problems

Scalarization of the fuzzy optimization problems using the embedding theorem and the concept of convex cone (ordering cone) is proposed in this paper. Two solution concepts are proposed by considering two convex cones. The set of all fuzzy numbers can be embedded into a normed space. This motivation naturally inspires us to invoke the scalarization techniques in vector optimization problems to solve the fuzzy optimization problems. By applying scalarization to the optimization problem with fuzzy coefficients, we obtain its corresponding scalar optimization problem. Finally, we show that the optimal solution of its corresponding scalar optimization problem is the optimal solution of the original fuzzy optimization problem.     

一类模糊线性规划模型的模糊最优区间值

讨论一类既有模糊不等式约束又有模糊等式约束的全模糊系数线性规划问题。在给定的模糊隶属度水平下 ,将模型转化为区间数线性规划模型 ,通过确定区间模型的最佳目标函数和最大可行域以及最劣目标函数和最小可行域 ,求出目标函数的模糊最优区间值 ,从而为决策者提供更多的决策信息。最后给出一个数值例子。     

Optimal stopping in a fuzzy environment

The problem under consideration is that of optimally controlling and stopping either a deterministic or a stochastic system in a fuzzy environment. The optimal decision is the sequence of controls that maximizes the membership function of the intersection of the fuzzy constraints and a fuzzy goal. The fuzzy goal is a fuzzy set in the cartesian product of the state space with the set of possible stopping times. Dynamic programming is applied to yield a numerical solution. This approach yields an algorithm that corrects a result of Kacprzyk.     

模糊聚类最优划分判定的一种新模型

针对聚类分析的模糊模式未解决的问题:模糊划分空间中模糊最优划分的判定问题,提出一个新的判定模型。给出基于新的最优划分判定模型的应用例子,验证了模型算法应用的可行性。     

An optimal control problem in the study of liver kinetics

The enzyme activities in the liver are described by a system of ordinary differential equations. A certain substance in the blood is transformed twice by different kinds of enzymes. The mathematical problem is to determine the distribution of the enzymes along the blood flow so that the outflow concentration of the once-transformed form of the substance is as small as possible. This problem has been considered before and solved for particular types of enzyme kinetics. In this paper, we solve the problem for more general types of kinetics (including substrate- inhibition kinetics). The methods used are also different, in that the problem is considered as a problem of optimal control and Pontryagin's maximum principle is applied to derive necessary conditions.     

Optimal Control of Magnetohydrodynamic Equations with State Constraint

This work is concerned with the maximum principle for optimal control problem governed by magnetohydrodynamic equations, which describe the motion of a viscous incompressible conducting fluid in a magnetic field and consist of a subtle coupling of the Navier-Stokes equation of viscous incompressible fluid flow and the Maxwell equation of electromagnetic field. An integral type state constraint is considered.