發(fā)布時(shí)間：2018-03-27 23:21

  本文選題：多屬性決策　切入點(diǎn)：不確定環(huán)境　出處：《湖北民族學(xué)院》2017年碩士論文

【摘要】：多屬性決策在軍事、工業(yè)工程、經(jīng)濟(jì)金融等領(lǐng)域有著廣泛應(yīng)用,一直是學(xué)術(shù)界研究的熱點(diǎn)問題。D數(shù)理論,作為D-S證據(jù)理論的推廣,因?yàn)閿U(kuò)展了表達(dá)不確定信息條件,近幾年廣泛應(yīng)用于多屬性決策問題中。然而,隨著研究的深入,發(fā)現(xiàn)D數(shù)理論還存在一些缺陷。因此,本文基于不確定環(huán)境下多屬性決策問題研究背景,從理論上進(jìn)一步完善D數(shù)理論,并結(jié)合變形蟲仿生算法將其應(yīng)用于路徑尋優(yōu)研究中,全文共分為五章。第一章主要介紹D-S證據(jù)理論,D數(shù)理論與多屬性決策的發(fā)展歷史以及他們?cè)谀壳皣?guó)內(nèi)外研究現(xiàn)狀,并對(duì)本文所研究的主要內(nèi)容給出相關(guān)準(zhǔn)備知識(shí)。第二章主要研究目前D數(shù)融合規(guī)則中不滿足交換律的問題,并依據(jù)D數(shù)自身所包含的已知信息,從評(píng)估等級(jí)以及相應(yīng)評(píng)估等級(jí)的信任程度兩個(gè)角度分別完善D數(shù)融合規(guī)則。通過應(yīng)用于環(huán)境評(píng)估的實(shí)例并將結(jié)果與前人文獻(xiàn)的對(duì)比研究表明,本文提出的方法能有效地解決多個(gè)D數(shù)融合不滿足交換律的問題,并可應(yīng)用于多屬性決策問題。第三章主要研究了D數(shù)集成公式中存在的一個(gè)不足,因?yàn)橹苯雍雎宰罱K評(píng)估結(jié)果的不完備信息而導(dǎo)致融合信息精確度降低并可能導(dǎo)致決策失誤。本章依據(jù)已經(jīng)獲得的評(píng)估結(jié)果并提出改進(jìn)方法,完善了D數(shù)理論的集成公式。通過對(duì)摩托車表現(xiàn)評(píng)估的實(shí)際例子驗(yàn)證表明,完善后的理論提高了決策的辨識(shí)度。第四章主要研究了D數(shù)理論在路徑尋優(yōu)中的應(yīng)用。將D數(shù)理論應(yīng)用于路徑尋優(yōu)問題中的道路評(píng)估指標(biāo)沖突、道路屬性值不完備以及限制必經(jīng)道路等情況下,結(jié)合仿生算法(變形蟲算法),分別建立幾種情況下的數(shù)學(xué)模型,并通過數(shù)值實(shí)驗(yàn)證明建立的模型能有效搜索到不確定環(huán)境下的最優(yōu)路徑,而且算法具有較低的復(fù)雜度。第五章總結(jié),對(duì)于本文研究工作進(jìn)行了討論并對(duì)未來研究提出了展望。
[Abstract]:Multi-attribute decision making, which is widely used in military, industrial engineering, economic and financial fields, has always been a hot topic in academic circles. As a generalization of D-S evidence theory, it extends the expression of uncertain information conditions. In recent years, it has been widely used in multi-attribute decision making. However, with the development of research, it is found that there are still some defects in the theory of D number. Therefore, this paper is based on the background of multi-attribute decision making in uncertain environment. The D number theory is further improved theoretically and applied to the path optimization research with the amoeba bionic algorithm. The first chapter mainly introduces the development history of D-S evidence theory and multi-attribute decision making, as well as their current research situation at home and abroad. In the second chapter, we mainly study the problem of not satisfying the commutative law in the current D-number fusion rules, and according to the known information contained in D-number itself, The D-number fusion rules are improved from the evaluation level and the degree of trust of the corresponding evaluation level, and the results are compared with the previous literatures by the example of environmental assessment. The method proposed in this paper can effectively solve the problem that multiple D-number fusion does not satisfy the commutative law, and can be applied to the multi-attribute decision making problem. Because the incomplete information of the final evaluation result is ignored directly, the accuracy of the fusion information is reduced and the decision error may be caused. The integration formula of D number theory is perfected. The actual example of motorcycle performance evaluation shows that, In chapter 4, the application of D number theory in path optimization is studied. In the case of incomplete road attribute value and restricted path, combined with bionic algorithm (amoeba algorithm), the mathematical models of several cases are established respectively. Numerical experiments show that the proposed model can effectively search the optimal path in uncertain environment, and the algorithm has lower complexity. Chapter five summarizes the research work in this paper and puts forward the prospect of future research.
【學(xué)位授予單位】：湖北民族學(xué)院
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：O225

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