本文關(guān)鍵詞： 不確定條件 項(xiàng)目組合選擇 項(xiàng)目調(diào)度 魯棒性 遺傳算法 STC啟發(fā)式算法 蒙特卡洛模擬　出處：《浙江大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

【摘要】：本文研究問(wèn)題是不確定條件下,資源受限項(xiàng)目組合選擇與調(diào)度問(wèn)題。項(xiàng)目組合選擇與項(xiàng)目調(diào)度作為項(xiàng)目管理的重要組成部分,正在受到越來(lái)越多的研究學(xué)者和項(xiàng)目經(jīng)理的重視。全球化的市場(chǎng)經(jīng)濟(jì)競(jìng)爭(zhēng)的激烈性和企業(yè)邊界內(nèi)部資源有限性,決定了企業(yè)必須選擇有限數(shù)量的項(xiàng)目,并完成對(duì)項(xiàng)目整個(gè)進(jìn)程計(jì)劃的有效控制。同時(shí),瞬息萬(wàn)變的經(jīng)濟(jì)狀態(tài)和激烈競(jìng)爭(zhēng)的市場(chǎng)環(huán)境,也暗示著企業(yè)或者組織面臨著比以往更多的不確定性,這也對(duì)項(xiàng)目組合選擇結(jié)果,進(jìn)度計(jì)劃的穩(wěn)定性和有效性提出了更高的要求�，F(xiàn)有的不確定條件下的項(xiàng)目組合選擇問(wèn)題研究多假設(shè)項(xiàng)目進(jìn)度生成計(jì)劃是確定的,是不考慮任務(wù)調(diào)度的項(xiàng)目組合問(wèn)題的研究,割裂了項(xiàng)目組合選擇與調(diào)度的內(nèi)在聯(lián)系；即使將項(xiàng)目組合選擇與調(diào)度聯(lián)系起來(lái),也多是在確定性條件下進(jìn)行分析,有一定的局限性。 本研究在以往研究的基礎(chǔ)上,著眼于不確定條件下,資源受限項(xiàng)目組合選擇與調(diào)度問(wèn)題的研究。本研究將項(xiàng)目組合選擇和項(xiàng)目調(diào)度兩個(gè)層面聯(lián)系起來(lái),在項(xiàng)目組合選擇層面,以項(xiàng)目組合期望收益和風(fēng)險(xiǎn)的組合函數(shù)為目標(biāo),進(jìn)行決策；在任務(wù)調(diào)度層面,對(duì)項(xiàng)目進(jìn)行魯棒調(diào)度；以期得到最優(yōu)的項(xiàng)目組合并提供具有魯棒性的多項(xiàng)目調(diào)度方案。不論是理論研究還是實(shí)踐意義,都具有一定程度的開(kāi)拓性。 本研究設(shè)計(jì)雙層決策方法對(duì)問(wèn)題進(jìn)行求解。其中,項(xiàng)目組合選擇作為上層決策問(wèn)題,采用遺傳算法對(duì)其求解,作為算法設(shè)計(jì)的主程序；項(xiàng)目任務(wù)調(diào)度層面作為下層決策,采用STC啟發(fā)式算法求解,作為算法設(shè)計(jì)的子程序,也是整個(gè)算法設(shè)計(jì)的內(nèi)核,進(jìn)行上層項(xiàng)目組合選擇決策時(shí),會(huì)被主程序反復(fù)調(diào)用；使用蒙特卡洛數(shù)字仿真的方法處理項(xiàng)目收益的不確定性,將項(xiàng)目任務(wù)調(diào)度執(zhí)行層面的魯棒性傳遞給項(xiàng)目組合選擇決策層面。 本研究不確定條件下的資源受限項(xiàng)目組合選擇與調(diào)度問(wèn)題,并設(shè)計(jì)了算例測(cè)試和大規(guī)模實(shí)驗(yàn)對(duì)算法進(jìn)行分析。研究表明,本研究設(shè)計(jì)的模型在處理不確定條件下的資源受限項(xiàng)目組合選擇問(wèn)題具有良好的適用性,設(shè)計(jì)的算法具有良好的求解質(zhì)量和求解效果。因此,本研究在一定程度上填補(bǔ)了不確定條件下,項(xiàng)目組合選擇與項(xiàng)目調(diào)度領(lǐng)域的理論研究空白,所設(shè)計(jì)的數(shù)學(xué)模型也可應(yīng)用于具體項(xiàng)目風(fēng)險(xiǎn)管理實(shí)踐過(guò)程中,具有理論和實(shí)踐意義。
[Abstract]:This paper studies the problem of resource constrained project portfolio selection and scheduling under uncertain conditions. Portfolio selection and project scheduling as an important part of project management. More and more researchers and project managers are paying more and more attention to it. The fierce competition in the global market economy and the limited resources within the enterprise boundary determine that enterprises must choose a limited number of projects. And complete the effective control of the whole process of the project. At the same time, the rapidly changing economic state and fierce competition market environment, also implies that enterprises or organizations are facing more uncertainty than ever before. This also puts forward higher requirements for the stability and effectiveness of the project portfolio selection results and schedule planning. The existing project portfolio selection problem under uncertain conditions multi-hypothesis project schedule generation plan is determined. It is the research of project portfolio problem that does not consider task scheduling, which separates the internal relation between project portfolio selection and scheduling. Even if portfolio selection is associated with scheduling, it is often analyzed under deterministic conditions, which has some limitations. On the basis of previous studies, this study focuses on the study of resource-constrained project portfolio selection and scheduling under uncertain conditions. This study links two levels of project portfolio selection and project scheduling. At the level of project portfolio selection, the goal is the combination function of the expected income and risk of the project portfolio, and the decision is made. At the task scheduling level, the project is scheduled robustly. In order to obtain the optimal project portfolio and provide a robust multi-project scheduling scheme, both theoretical research and practical significance have a certain degree of pioneering. In this study, a two-layer decision making method is designed to solve the problem, in which the project combination is chosen as the upper decision problem, and the genetic algorithm is used to solve the problem, which is the main program of the algorithm design. Project task scheduling level as the lower level decision, using STC heuristic algorithm to solve, as the algorithm design subroutine, but also the kernel of the whole algorithm design, when the upper project combination selection decision. Will be called repeatedly by the main program; Monte Carlo digital simulation is used to deal with the uncertainty of project income, and the robustness of project task scheduling execution level is transferred to the decision level of project portfolio selection. In this paper, the resource constrained project portfolio selection and scheduling problem under uncertain conditions is studied, and an example is designed to test and analyze the algorithm. The model designed in this paper has good applicability in dealing with the resource-constrained project portfolio selection problem under uncertain conditions, and the algorithm designed has good solution quality and solution effect. To a certain extent, this study fills the blank of theoretical research in the field of portfolio selection and project scheduling, and the mathematical model designed can also be applied to the practical process of specific project risk management. It has theoretical and practical significance.
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：F272

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