Qfd system parameters identification based on fuzzy program 系統(tǒng)參數(shù)確定方法
Fuzzy programming method of security portfolio 證券組合投資的模糊規(guī)劃方法
New methods for fuzzy programming problems based on order structure 基于序結(jié)構(gòu)的模糊規(guī)劃問題求解方法
Application of fuzzy programming to optimization of bench blasting parameters of surface mines 模糊規(guī)劃原理與露天礦臺階爆破參數(shù)優(yōu)化
Chapter 3 of this thesis discusses schedule management in detail , analyses some methods to make schedule plan , for example , gantt , cmp , and pert , points out their advantages and disadvantages . then the thesis puts forward a fuzzy program evaluation and review technique 在第三章中,就項目管理中的進度管理進行了詳細的討論,分析了進度計劃的幾種主要方法(甘特圖法、關(guān)鍵路徑法、計劃評審技術(shù)等) ,并指出了這幾種方法的優(yōu)缺點。
This paper studies the ways to comfotmate the models of portfolio investment combi - nation , and demonstration analysis , divided into three parts . the first part : exordium . mainly introduces the risk of portfolio investment . the second part : brings forward several kinds of investment combination model , including the traditional markowitz model , multiobjective programming and fuzzy programming . the third part : goes along with the demonstration analysis of each kind of model basted on the shanghai stock market , at the same time , appraises the superiority and inferiority with the single - parameter measurement of tangible achievement . before then , most papers discussed the static models , this paper extends the static models to the dynamic models by the means of weighted moving average and bayes estimation 本文研究了證券投資組合模型的構(gòu)造方法及其實證分析,分三部分進行:第一部分,緒論,主要介紹證券投資的風(fēng)險;第二部分,提出幾種投資組合模型,在傳統(tǒng)的馬柯維茨模型及線性規(guī)劃的基礎(chǔ)上,本文另外提出多目標規(guī)劃的其它解法,并把前人模糊規(guī)劃的理論應(yīng)用到具體的建模中;第三部分,根據(jù)我國的滬市行情,對各種模型進行實證分析,并利用實績的單參數(shù)度量對各種模型的優(yōu)劣性進行評價。
Secondly , we give the mathematic fuzzy environment and satisfactory decision - making . then make a summary of the method how to resolve a satisfying optimization problem , finally , we research a kind of method based on fuzzy programming to solve a satisfied optimization problem with some constrains and this method has been verified by the simulation results 在此基礎(chǔ)上對一類模糊不確定環(huán)境中存在生產(chǎn)約束時的滿意優(yōu)化控制問題,在預(yù)測控制的框架下把具有模糊邊界約束的有限預(yù)測時域的優(yōu)化問題轉(zhuǎn)化為等價的確定性規(guī)劃問題,并且進行了仿真,仿真結(jié)果表明了該算法是有效的。
The conclusion is : multiobjective programming and fuzzy programming are superior to the traditional markowitz model , compart : s the dynamic models with the static models , the former can reponse more soon to the wave of the stock price , so we can adjust period by period based on the dynamic models 本文得出的結(jié)論是:多目標規(guī)劃及模糊規(guī)劃等方法優(yōu)于傳統(tǒng)的馬柯維茨模型,在實證檢驗中表現(xiàn)出更高的投資效率,動態(tài)的模型與靜態(tài)的模型相比,能更快地對股價波動作出反應(yīng),可進行逐期調(diào)整。
Traditional uncertain programming mainly contains stochastic programming and fuzzy programming , which have many applications in manufacture , economy and management etc . especially , the theory of stochastic or fuzzy linear programming is more complete , so it has more applications than stochastic or fuzzy nonlinear programming 傳統(tǒng)的不確定規(guī)劃主要分為兩大類:隨機規(guī)劃和模糊規(guī)劃,并且在生產(chǎn)、經(jīng)濟及管理等諸多方面已有廣泛的應(yīng)用,特別是隨機線性規(guī)劃和模糊線性規(guī)劃理論較為完善,應(yīng)用更加廣泛。