资源分配的多目标模糊优选动态规划分析法

本尝试应用多目标模糊优选动态规划分析法求解具有多个量纲不一的定量评价目标,或既有定量目标又有定性目标的有限资源分配问题。     

基于模糊优选决策的炮兵火力分配模型研究

将模糊优选决策方法应用于炮兵战场火力分配,综合考虑影响火力分配的各种因素,建立模糊优选决策矩阵,等到优化分配的模型.     

多维多目标模糊优选动态规划及其在资源分配中的应用

将目前所研究的一维模糊优选动态规划扩展为多维模糊优选动态规划。在求解多维多阶段问题时,采用遗传算法与模糊动态规划法相结合进行求解,保证了优化变量的全局最优性。在其中权系数的处理中,本文采用了主客观综合评定的方法,保证了数据的合理性及准确性。并且文中用此方法解决了多维多阶段多目标的资源分配问题。     

动态模糊规划模型的构建及应用

常规规划模型通常存在如下两种缺陷:首先,它的目标系数及约束条件都是在硬性限制下的确定值,因而在建模方面弹性小、硬度大;其次,它的目标系数与时间无关,因此不能有效地刻划时时刻刻变化着的目标系数,而动态模糊规划模型可以有效地解决上述缺陷.首先应用模糊动态AHP确定目标系数;然后根据L-R模糊数的强序关系准则,将动态模糊规划模型分解为最优与最劣两个模糊规划模型;再根据以α水平截集为基础的求解方法,将上述两个模型进行相应的转换,建立具有风险分析功能的动态模糊规划模型;最后将其应用到一个实际算例中,收到较好的结果.     

模糊优选理论与模型

本文提出了综合评判优选的新途径,提出模糊优选理论,并建立起相应的计算模型,可根据实际问题的需要而选用。     

模糊优选（优化）理论与模型

本文提出的多目标系统模糊优选(优化)理论与计算模型,是处理多目标系统的一个新的优化方法。     

权监督多级模糊优选模型

本从多级模糊优选概念出发，建立一种以决策经验，偏好为监督，在方案优选确定过程中融合主、客观权重，同时确定评价指标权重和决策方案优属度的权监督多级模糊优选算法。     

采购量分配决策模糊规划模型

供应商对形成企业的竞争力起着关键性的作用。采购决策中,采购商需要决策两方面的问题:应该选择哪些供应商以及在每一供应商应该采购多少。本文考虑了多目标性和目标的模糊性,同时为供应商选择和采购量分配提出了一个集成的决策模型。最后,通过一个算例阐释了该模型。     

博弈联盟模糊收益的分配

提出了联盟模糊收益合理分配的一种新方法.首先,在模糊收益α截集上定义了α合理分配集,分析了该分配集与模糊收益Shapley值的关系.接着,给出了模糊收益的α合理Shapley分配函数,对其性质进行了讨论.然后,构造了模糊合理Shapley分配,证明其连续性,得到了联盟模糊收益与模糊合理Shapley分配具有包含关系的结论.     

一般化两人零和模糊对策的模糊规划法

本文在充分考虑局中人的策略集是模糊子集的基础上,给出更一般化的具有模糊支付与模糊赢得的两人零和模糊对策的模糊规划模型。利用模糊数的序方法,得到了此对策求解问题可以转化为带有模糊参数的两个经典规划的求解问题。文末给出算例予以说明。     

Optimization of Multilevel Investments Using Dynamic Programming Based on Fuzzy Cash Flows

Dynamic programming is applicable to any situation where items from several groups must be combined to form an entity, such as a composite investment or a transportation route connecting several districts. The most desirable entity is constructed in stages by forming sub-entities of progressively larger size. At each stage of the development, the sub-entities that are candidates for inclusion in the most desirable entity are retained, and all other sub-entities are discarded. In deterministic dynamic programming, a specification of the current state and current decision is enough to tell us with certainty the new state and costs during the current stage. In many practical problems, these factors may not be known with certainty, even if the current state and decision are known. In this paper, the dynamic programming is applied to the situation where each investment in the set has the following characteristics: the amount to be invested has several possible values, and the rate of return varies with the amount invested. Each sum that may be invested represents a distinct level of investment, and the investment therefore has multiple levels. A fuzzy present worth based dynamic programming approach is used. A numeric example for a multilevel investment with fuzzy geometric cash flows is given. A computer software named FUZDYN is developed for various problems such as alternatives having different lives, different uniform cash flows, and different ranking methods.     

Envelope Theorems in Dynamic Programming

The envelope theorem is a statement about derivatives along an optimal trajectory. In dynamic programming the envelope theorem can be used to characterize and compute the optimal value function from its derivatives. We illustrate this here for the linear-quadratic control problem, the resource allocation problem, and the inverse problem of dynamic programming.     

警车配置及巡逻方案研究

以警车的配置与巡逻方案为研究对象,建立了一套警车巡逻模型,并提出巡逻效果显著度及隐藏性的评价标准,分别针对警车初始位置配置与巡逻方案的制定,提出警车配置优化选址的贪婪算法与基于多Agent的警车巡逻方案设计方法,给出了不同情景下的配置及巡逻方案:①在只考虑警车选址配置的情况下,配置19辆警车可以使全市路网警车覆盖率达到92.8%;②在顾及巡逻效果显著性与隐藏性的情况下,配置25辆警车使全市路网在整个巡逻过程中平均警车覆盖率达到90.9%;③在配置10辆警车的情况下,使得全市路网在整个巡逻过程中平均警车覆盖率达到61.5%.     

求解多层线性规划的模糊规划法

本文用模糊集理论中的隶属函数描述多层线性规划的各层目标,在第一层给定最小满意水平下,通过求解相应层次的模糊规划来确定各层的最小满意度,从而最终得到问题的一个满意解。提出的方法只需求解一系列线性规划问题,具有较好的计算复杂性和可行性,最后的算例进一步验证了方法的有效性。     

Allocation of dependent divisional resources

A resource allocation problem is considered with resources that are dependent in the sense that an allocation to an activity requires the application of several resources, except for certain activities which are divisional in the sense that an allocation to such an activity requires the use of only a single resource. Return and cost functions are assumed to be continuous and increasing, and the allocation variables are continuous. Conditions are given for the replacement of the continuous problem by an associated problem with discrete variables and a single constraint, and to a given degree of accuracy. The associated problem can be efficiently solved by dynamic programming. Certain divisional resource allocation problems with discrete variables and several linear constraints are shown to be equivalent to a discrete problem with a single constraint. A numerical example is given.