本文選題：魯棒性項目調(diào)度 + 質(zhì)量魯棒性�。� 參考：《華中科技大學》2014年博士論文

【摘要】：由于市場環(huán)境快速變化,項目特別是大型工程項目所涉及的不確定性因素日益增多,使越來越多的項目出現(xiàn)問題,如費用超支、超出工期甚至中途夭折等。與此同時,現(xiàn)代項目管理又要求周期更短、準時完工率更高、成本更低。在這種情況下,應對復雜環(huán)境中出現(xiàn)的各種不確定因素,保證項目按計劃按時完工而形成的魯棒性項目調(diào)度,引起了企業(yè)界和學術(shù)界的廣泛關(guān)注,成為項目管理領(lǐng)域理論研究的熱點。時間緩沖技術(shù)是建立魯棒性項目調(diào)度計劃的主要方法,主要有關(guān)鍵鏈集中緩沖方法和分散緩沖方法。對這兩種緩沖方法進行研究,建立合理的魯棒性計劃,成為該領(lǐng)域的重點問題。本文綜合應用雙目標優(yōu)化、啟發(fā)式算法及系統(tǒng)仿真等方法,對二種緩沖的適用環(huán)境及其相應的魯棒性項目調(diào)度計劃進行了系統(tǒng)深入的研究,主要研究工作如下： 首先,綜合考慮項目執(zhí)行環(huán)境中不確性因素,如活動時間確定性程度、項目交貨期限,按時完工重要性等,分別運用集中緩沖和STC分散緩沖方法,制定魯棒性項目調(diào)度計劃,在仿真環(huán)境下執(zhí)行該計劃,對比二種緩沖方法的魯棒性績效指標。結(jié)果表明：分散緩沖法具有更好的解魯棒性；當活動時間的不確定性程度較大時,集中緩沖法的質(zhì)量魯棒性較好；當項目工期較緊的情況下,分散緩沖法具有更好的魯棒性。 然后,針對不同的項目網(wǎng)絡特征,研究二種緩沖方法的適用性。綜合考慮項目規(guī)模、網(wǎng)絡復雜度等因素,生成不同的項目實例,并利用兩種緩沖方法分別制定魯棒性項目調(diào)度計劃,模擬不確定環(huán)境下項目計劃的執(zhí)行。仿真結(jié)果表明：當活動時間不確定程度較小時,在小規(guī)模簡單的項目中,分散緩沖魯棒性優(yōu)于集中緩沖,這時優(yōu)先選擇分散緩沖法制定魯棒性項目調(diào)度計劃。當項目規(guī)模較大且網(wǎng)絡復雜時,或在項目不確性程度較大時,集中緩沖的質(zhì)量魯棒性始終優(yōu)于分散緩沖,這時應優(yōu)先選擇集中緩沖法。 接著研究了雙目標魯棒性項目調(diào)度算法。為使項目既保證按時完工又能按計劃執(zhí)行,同時考慮解魯棒性和質(zhì)量魯棒性,并以STC分散緩沖為基礎,構(gòu)建了雙目標魯棒性調(diào)度模型。綜合運用模擬退火和禁忌搜索算法,提出了求解這種雙目標魯棒性調(diào)度問題的二階段算法。實驗結(jié)果表明,本文所提出的算法搜索過程較快穩(wěn)定性較好,所得解優(yōu)于單智能算法解,能夠根據(jù)管理者的魯棒性偏好獲得雙目標調(diào)度問題的近優(yōu)解。 最后,對非關(guān)鍵鏈溢出和關(guān)鍵鏈斷裂情況下的關(guān)鍵鏈計劃進行研究。針對關(guān)鍵鏈計劃插入接駁緩沖后出現(xiàn)資源再次沖突、關(guān)鍵鏈斷裂、非關(guān)鍵鏈溢出等問題,提出兩種解決方案。第一種方案從緩沖設置方式的視角進行研究,用分散緩沖方法替代集中緩沖,最后通過項目管理數(shù)據(jù)庫(PSPLIB)中大量實例,證明該方法的普遍適用性及其在完工和計劃魯棒性方面的優(yōu)勢。第二種方案用二階段啟發(fā)式算法對出現(xiàn)問題的關(guān)鍵鏈計劃直接進行重排：第一階段運用動態(tài)規(guī)劃和三種重排優(yōu)先級規(guī)則對計劃進行重排來消除資源沖突。針對重排后仍然存在關(guān)鍵鏈斷裂或非關(guān)鍵鏈溢出的項目,運用第二階段提出的啟發(fā)式算法,進行二次重排,得到合理的關(guān)鍵鏈計劃。最后,經(jīng)過單項目和大量項目仿真實驗證實,該方案能夠有效解決大部分項目的關(guān)鍵鏈重排存在的問題,且所制定的關(guān)鍵鏈進度計劃在仿真執(zhí)行中具有更好的完工性績效。
[Abstract]:Due to the rapid change of the market environment , the uncertainty factors involved in the project , especially the large - scale project , have caused more and more project problems , such as overspending of the cost , higher on - time completion rate and lower cost . At the same time , the modern project management requires shorter cycle , higher on - time completion rate and lower cost .

Firstly , the uncertain factors of the project execution environment , such as the degree of certainty of the activity time , the time limit of the project , the importance of time completion , etc . are comprehensively considered , and the robust project scheduling plan is formulated by using the centralized buffer and STC dispersion buffer method respectively , and the robustness performance indexes of the two buffering methods are compared under the simulation environment .
when the degree of uncertainty of the activity time is large , the quality robustness of the concentrated buffer method is better ;
The decentralized buffer method has better robustness when the project duration is tight .

Then , the applicability of two kinds of buffering methods is studied for different project network characteristics . Considering the factors such as project size and network complexity , different project instances are generated , and the implementation of the project plan under the environment is simulated . The simulation results show that , when the project size is large and the network is complicated , or when the project is not true , the quality robustness of the centralized buffer is always better than the decentralized buffer , and then the central buffering method should be preferred .

A two - stage algorithm for solving the problem of double - target robust scheduling is proposed by using simulated annealing and tabu search algorithm . The results show that the proposed algorithm is better in stability and better than single intelligent algorithm , and can obtain the near optimal solution of double - target scheduling problem according to the robustness preference of the manager .

In the end , the key chain plans in the case of non - critical chain overflow and critical chain fault are studied . Two solutions are proposed for the key chain plans . First , the key chain plans of the problem are rearranged by using dynamic programming and three rearrangement priority rules . Finally , through single project and large number of project simulation experiments , this scheme can effectively solve the problem of key chain rearrangement in most projects , and the key chain schedule plan has better completion performance in simulation execution .
【學位授予單位】：華中科技大學
【學位級別】：博士
【學位授予年份】：2014
【分類號】：TU71

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