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一种基于层次分析法的公务员购车决策模型

论文编号:XXLW009论文字数:11274,页数:31

摘 要

本文在分析公务员购买车辆过程中所需要注意的多种因素的基础上,结合宁海县公务员购买车辆的实际情况,构建了一套适用评价车辆综合性能的指标体系,提出了一种基于层次分析法的公务员购车决策模型。本文在多位专家的指导下对所调查到的宁海县公务员购买车辆的基本资料进行统计与分析,构造出两两比较的判断矩阵。利用合积法求出矩阵的最大特征值,并结合Matlab对其最大特征值进行检验。验证各矩阵是否具有满意的一致性,以确保判断矩阵的可靠性,求出各种因素相对于上一层次的权重。最后将专家对三种车型各因素评测的数据与各因素相对与总目标的权值相结合,对三种车型进行综合性能的实例分析,作出对车型选择的优先顺序并得出了一些结论和解释。为公务员在购买车辆时对车辆综合性能的判断以及最终决策提供了借鉴。

关键词:公务员 层次分析 数学模型 Matlab

A purchase car decision model of civil servant based on analytic hierarchy process

Abstract

The article construct a range of target system to evaluate the combination property of cars and porpose a purchase car decision model of civil servant based on analytic hierarchy process.Based on a variety of factors in the analysis of civil servants in the course of the purchase of cars,combine with the actual situation of purchasing cars by civil servants in Ninghai.In this paper,construct a pairwise comparison matrix based on the statistics and analysis of purchasing cars by civil servants in Ninghai.We obtained the largest eigenvalue and combined with Matlab to test the the largest eigenvalue.Verify that whether the matrix has the satisfying consistency and to ensure the reliability of the matrix,calculate the weighting that the various factors relative to the upper ones.Finally ,combine the evaluating data of the three models’factors and the weighting that the factors relative to the general objevtive to analyze the combination property of the three car models.Also work out the priorities of choosing the model and obtain some conclusions and explanations.Provide the benchmark for civil servant to decide the combination property of cars when purchasing.

Keywords:civil servant; analytic hierarchy process;mathematical model; Matlab

目 录

中文摘要ⅰ

英文摘要ⅱ

目录ⅲ

第一章 前言1

第二章 AHP层次分析模型 2

2.1 层次分析法的基本原理2

2.2 层次分析法的优点2

2.3 层次分析法的步骤3

2.3.1 建立递阶层次结构3

2.3.2 构造判断矩阵4

2.3.3 相对权重的计算7

2.3.4 层次单排序以及一致性检验10

2.3.5 层次总排序以及一致性检验20

第三章 公务员购车实例分析23

第四章 结果分析24

致谢25

参考文献26

附录I 《影响购车决策因素的重要性调查问卷》27

一种基于层次分析法的公务员购车决策模型......