本文關(guān)鍵詞： 動(dòng)態(tài)需求引導(dǎo) 多目標(biāo)推理模型 產(chǎn)品配置Nash均衡 決策優(yōu)化　出處：《合肥工業(yè)大學(xué)》2016年碩士論文　論文類型：學(xué)位論文

【摘要】：在個(gè)性化產(chǎn)品定制中,大數(shù)據(jù)背景下,針對(duì)客戶需求信息的動(dòng)態(tài)、不完備等情況,企業(yè)越來(lái)越關(guān)注對(duì)客戶需求最大程度的滿足,實(shí)現(xiàn)產(chǎn)品的最優(yōu)配置。如何既實(shí)現(xiàn)對(duì)客戶動(dòng)態(tài)需求的實(shí)時(shí)引導(dǎo),又能夠解決產(chǎn)品配置中客戶滿意度和企業(yè)產(chǎn)品成本沖突問(wèn)題,是當(dāng)前企業(yè)急需解決的問(wèn)題。結(jié)合計(jì)算機(jī)技術(shù),對(duì)客戶需求信息進(jìn)行處理并采用合理的需求引導(dǎo)機(jī)制,然后利用合理的產(chǎn)品配置推理方法,是解決這類問(wèn)題的重要手段,也是實(shí)現(xiàn)個(gè)性化定制生產(chǎn)的關(guān)鍵。本文研究了客戶需求的相關(guān)問(wèn)題,引入了蟻群算法機(jī)制和博弈理論,建立了基于蟻群算法的客戶動(dòng)態(tài)需求引導(dǎo)機(jī)制和基于Bayes-Nash均衡的產(chǎn)品配置多目標(biāo)推理模型,對(duì)產(chǎn)品配置Nash均衡的求解、配置方案的決策優(yōu)化進(jìn)行了深入研究,具體內(nèi)容如下：1)針對(duì)客戶需求信息的特征,研究客戶需求信息的獲取方法；對(duì)客戶需求進(jìn)行了規(guī)范化處理,將客戶需求分為靜態(tài)需求和動(dòng)態(tài)需求,建立多域間功能層次清晰的需求節(jié)點(diǎn)交互關(guān)聯(lián)結(jié)構(gòu)并進(jìn)行賦權(quán)處理,將模糊、不完備的客戶需求信息轉(zhuǎn)化為明確、可用的客戶需求向量。2)針對(duì)不完備的客戶動(dòng)態(tài)需求,為了客戶需求正確表達(dá)及保證產(chǎn)品配置的可行性,引入蟻群算法機(jī)制,建立了基于蟻群算法的客戶動(dòng)態(tài)需求引導(dǎo)機(jī)制。提出產(chǎn)品可配置節(jié)點(diǎn)和功能需求節(jié)點(diǎn),研究節(jié)點(diǎn)間的映射關(guān)系,建立產(chǎn)品可配置模型。研究蟻群算法的行為機(jī)制,實(shí)現(xiàn)對(duì)客戶動(dòng)態(tài)需求信息的實(shí)時(shí)引導(dǎo)。3)針對(duì)機(jī)械產(chǎn)品配置中客戶滿意度和企業(yè)產(chǎn)品成本沖突問(wèn)題,引入Bayes-Nash均衡理論,建立產(chǎn)品多域節(jié)點(diǎn)之間的均衡模型;以企業(yè)和客戶作為決策主體,企業(yè)產(chǎn)品成本和客戶滿意度作為博弈的收益函數(shù),在結(jié)構(gòu)、性能和成本域相似度最大值搜索的基礎(chǔ)上確定博弈雙方的策略集,最后,給出產(chǎn)品配置Nash均衡的檢驗(yàn)標(biāo)準(zhǔn),對(duì)產(chǎn)品配置方案進(jìn)行決策分析。4)提出了產(chǎn)品配置Nash均衡求解方法,改進(jìn)模擬退火算法,對(duì)產(chǎn)品配置多目標(biāo)推理中Nash均衡點(diǎn)進(jìn)行實(shí)時(shí)求解。5)提出基于變型設(shè)計(jì)決策優(yōu)化方法,解決產(chǎn)品配置多目標(biāo)推理中無(wú)Nash均衡點(diǎn)的問(wèn)題從而實(shí)現(xiàn)產(chǎn)品配置決策的優(yōu)化；提出基于Pareto客戶需求引導(dǎo)決策優(yōu)化方法,解決引導(dǎo)過(guò)程中空路徑的問(wèn)題從而實(shí)現(xiàn)需求引導(dǎo)決策的優(yōu)化。
[Abstract]:In product customization, under the background of big data according to the customer demand information, dynamic, incomplete, enterprises pay more and more attention to the maximum to meet customer needs, to achieve the optimal allocation of products. How to realize the real-time guidance of customer demand and dynamic, can solve in the configuration of product customer satisfaction and enterprise product cost the conflict is the current urgent. Combined with computer technology, customer demand for information processing and using reasonable demand guide mechanism, product configuration reasoning method and reasonable use, is an important means to solve this problem, it is also the key to customization production. This paper introduces the issues about customer demand the introduction of the ant colony algorithm, mechanism and game theory, established the dynamic customer demand based on ant colony algorithm and guide mechanism based on Bayes-Nash equilibrium production Product configuration multi-objective reasoning model of product configuration is Nash balanced, in-depth research on decision making optimization program, the specific contents are as follows: 1) according to the characteristics of customer demand information acquisition method of the customer demand information; customer demand for the standardization process, customer demand will be divided into static and dynamic demand the establishment of functional requirements, a clear hierarchy of needs interaction structure and node weighted fuzzy, multi domain, customer demand for incomplete information into clear, available customer demand vector.2) according to the customer demand dynamic incomplete, in order to correct customer demand expression and ensure the feasibility of the product configuration, the ant colony algorithm mechanism the establishment of the guide mechanism, dynamic customer demand based on ant colony algorithm is proposed. Product configuration node and the functional requirements of node mapping relationship between nodes, construction Can establish product configuration model. The behavior mechanism of ant colony algorithm, to achieve real-time guide.3 on dynamic customer demand information) for customer satisfaction and product configuration in machinery enterprise product cost conflict, the introduction of Bayes-Nash equilibrium theory, establish the equilibrium model between product multi domain nodes; to the enterprise and the customer as the decision-making body, the enterprise product cost and customer satisfaction as the revenue function, the game in the structure, performance and cost of search domain similarity value is determined based on the both sides of the game strategy set, finally, gives the product configuration of Nash equilibrium test, decision analysis of.4 product configuration) proposed product configuration Nash equilibrium method, the improved simulated annealing algorithm real time.5 to solve the Nash equilibrium point of product configuration reasoning) proposed multi-objective decision optimization method based on variant design, product configuration solution In the multi-objective reasoning, there is no Nash equilibrium point, so as to achieve the optimization of product configuration decision. Based on the Pareto customer needs guidance decision-making optimization method, we solve the problem of the hollow path in the guidance process, so as to achieve the optimization of demand guidance decision-making.

【學(xué)位授予單位】：合肥工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：F273;TP18;F224.32

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