【正文】 矩陣；聚合；優(yōu)化1引言作為一個有效的方法用于多目標和多因素決策、層次分析法已經(jīng)廣泛應(yīng)用于許多決策方面。步驟6：在（N1）中使用加法合成得到，并建立綜合判斷矩陣A *，應(yīng)用該方法的總結(jié)，計劃最終排序。 Optimization1 IntroductionAs an effective method utilized in multiobjective and multifactor decision making, Analytic Hierarchy Process has been widely applied in many decision making aspects. It normally involves several decision makers, therefore, multiple judgment matrixes provided by different decision maker need to be aggregated so that to reach a more reasonable solution. In the field of matrix aggregation, Lv Yuejin and Guo Xinrong utilized the Connected Undirected Graph and its theories, by excluding the biased expert judgments, have e up with a reciprocal judgment matrix aggregation method which was oriented from the theory of mth power graph of simple undirected connected graph [1]. Nevertheless,Liu Xin and Yang Shanlin developed Hadamard convex bination based on judgment matrix [23], provided the evidence on “additive”and“multiplicative” convex binations consistency improvement as well. The document [4] has studied on the optimization principle related with the convex coefficients of judgment matrix, and provided solution to the convex bination coefficients of judgment matrix.Different matrix aggregation schemes will process the expert judgment data with discrepancy and aggregation results of judgment matrix are produced differently, therefore the weight and consistency after calculation are differential from another. While, in the process of matrix aggregation, the same aggregation schemes also present discrepantly in different judgment matrix aggregation. In the practice of solving problems, it is necessary to adopt different matrix aggregation methods and implement relevant verification and choice. This paper will investigate the feasibility and problems of matrix aggregation schemes that are initiated from graph theory and Hadamard convex binations, andrelevant verification, optimizing and choice have been made.2 The Description of Matrix Aggregation Method The Solution of Matrix Aggregation Method Based on Graph TheoryMatrix aggregation solution based on graph theory, is to set up a level deviation matrix E, and select more consistent factors from the different expert judgment matrix A(k), so as to construct a plete consistent judgment matrix A*. The detailed construction steps and explanation see document [1].Step1: Setting up the expert judgment matrix with consistency A1Am；Step2: Setting up the grade deviation matrix in decisionmaking process， Supported by colleges and universities natural science research project of AnhuiProvince, china (KJ2012Z054) 。省略細節(jié)流程,得到無向圖的連接圖2和圖3。本文將探討矩陣的可行性和存在的問題,從聚合方案啟動圖論和阿達瑪凸組合,做出相關(guān)的驗證、優(yōu)化和選擇。不同的矩陣集合計劃將處理專家判斷數(shù)據(jù)、差異和聚合導(dǎo)致判斷矩陣的產(chǎn)生方式不同,因此在計算重要性和一致性是不同與另一方面。 1圖1所示。are defined as follows:If C=A⊕ B，so，if C=A運算符⊕定義如下若C=A⊕ B那么；若C=A 畢業(yè)設(shè)計 （外文翻譯）畢 業(yè) 設(shè) 計（論文）題 目： Application of Matrix Aggregation Method in Group Decision Making Process學(xué) 院： 數(shù)理學(xué)院 專業(yè)名稱： 信息與計算科學(xué) 學(xué) 號： 200941210104 學(xué)生姓名： 石夢弟 指導(dǎo)教師： 明廷橋 2013年2月20日矩陣聚合方法在群體決策過程的應(yīng)用周威廉（合肥科技大學(xué)經(jīng)濟管理學(xué)院，安徽合肥）