本文關(guān)鍵詞：重復(fù)性項(xiàng)目時(shí)間費(fèi)用權(quán)衡模型及其擴(kuò)展研究　出處：《華北電力大學(xué)(北京)》2016年博士論文　論文類型：學(xué)位論文

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【摘要】：時(shí)間費(fèi)用權(quán)衡是一類在項(xiàng)目調(diào)度領(lǐng)域廣泛研究且具有重要應(yīng)用價(jià)值的優(yōu)化問題,旨在滿足給定截止日期條件下最小化項(xiàng)目的總費(fèi)用。重復(fù)性項(xiàng)目是指施工場所可劃分為若干獨(dú)立的單元,部分或全部工序需要在多個(gè)單元上重復(fù)執(zhí)行的項(xiàng)目。常見的例子有高層建筑、高速公路、管道工程和住宅開發(fā)等。本文的研究目的是為重復(fù)性項(xiàng)目時(shí)間費(fèi)用權(quán)衡問題(TCTPRP問題)建立可計(jì)算的數(shù)學(xué)模型。又因?yàn)門CTPRP問題屬于NP-hard問題(即,不存在多項(xiàng)式時(shí)間可解的算法),因此本文還將研究能解決較大規(guī)模問題的近似模型或者啟發(fā)式方法。與非重復(fù)性項(xiàng)目相比,重復(fù)性項(xiàng)目調(diào)度的復(fù)雜性主要表現(xiàn)在決策變量的多樣化上,即它可能需要計(jì)算工序的執(zhí)行模式、工作隊(duì)的雇傭數(shù)量、單元間的邏輯順序和單元的分配方案等。理論上,一個(gè)完美的TCTPRP模型或算法需要具備同時(shí)處理多工作隊(duì)、多模式和非固定邏輯順序(也稱為軟邏輯)的能力。但是,實(shí)際工程中并不是所有的項(xiàng)目都能夠或者有必要雇傭多個(gè)工作隊(duì)、考慮多種執(zhí)行模式或者隨意改變單元間的邏輯順序。因此,從迎合實(shí)際的角度,本文同已有研究一樣考慮不同類型限制條件下的TCTPRP問題。本文的主要研究內(nèi)容和研究成果如下：(1)在單模式和固定邏輯條件下研究多工作隊(duì)TCTPRP問題,目標(biāo)是確定所有工序最優(yōu)的工作隊(duì)雇傭數(shù)量及其在各單元上的開始時(shí)間。我們提出了基于混合整數(shù)線性規(guī)劃的精確模型,并在考慮工序進(jìn)度不變假設(shè)條件下,建立了能在短時(shí)間內(nèi)處理較大規(guī)模問題的近似模型。數(shù)值實(shí)驗(yàn)表明,精確模型在限定的時(shí)間(1小時(shí))內(nèi)能解決的最大規(guī)模問題包含50個(gè)工序、100個(gè)單元和10個(gè)工作隊(duì)；近似模型計(jì)算結(jié)果的平均偏差不超過1%,并且能在短時(shí)間內(nèi)處理包含100個(gè)工序的項(xiàng)目。然后,我們將上述精確模型推廣至非典型項(xiàng)目(即,工序在不同單元上的工期可以不相同的項(xiàng)目),并提出了能計(jì)算工序最優(yōu)單元分配方案的擴(kuò)展模型。(2)在單工作隊(duì)和固定邏輯條件下研究多模式TCTPRP問題,目標(biāo)是確定所有工序最優(yōu)的執(zhí)行模式及其在各單元上的開始時(shí)間。我們同樣提出了基于混合整數(shù)線性規(guī)劃的精確模型,并定義了兩種模式消除規(guī)則,它們能有效識(shí)別并刪除不可行或者非最優(yōu)的工序執(zhí)行模式,從而降低模型的求解難度。對(duì)于較大規(guī)模的問題,我們提出了基于線性規(guī)劃松弛思想的兩階段的啟發(fā)式算法。數(shù)值實(shí)驗(yàn)表明,精確模型在可接受的時(shí)間內(nèi)能處理的最大規(guī)模問題包含60個(gè)工序、40個(gè)單元和20種執(zhí)行模式；啟發(fā)式算法計(jì)算結(jié)果的平均偏差不超過4%并且有能力解決更大規(guī)模的問題。(3)研究單工作隊(duì)多模式軟邏輯TCTPRP問題,目標(biāo)是確定單元間的最優(yōu)邏輯順序,以及所有工序最優(yōu)的執(zhí)行模式及其在各單元上的開始時(shí)間。我們分析了軟邏輯對(duì)重復(fù)性調(diào)度可能產(chǎn)生的影響,并在此基礎(chǔ)上給出了用于描述該問題的混合整數(shù)非線性規(guī)劃模型�？紤]到模型的求解難度,我們提出了基于遺傳算法和線性規(guī)劃的啟發(fā)式方法。已有文獻(xiàn)只對(duì)典型項(xiàng)目下多工作隊(duì)TCTPRP問題以及單工作隊(duì)和固定邏輯下的多模式TCTPRP問題進(jìn)行了研究,并且它們均采用智能算法作為求解工具,不能保證解的最優(yōu)性。我們的工作在一定程度上彌補(bǔ)了已有文獻(xiàn)的不足,并且數(shù)值實(shí)驗(yàn)的結(jié)果還能作為參考用于評(píng)價(jià)其他啟發(fā)式方法的性能。
[Abstract]:Time cost trade-off is a kind of optimization in the field of project scheduling and extensive research has important application value, to meet the given deadline under the condition of minimizing the total cost of the project. The repetitive project refers to the construction sites can be divided into several independent units, all or part of the process shall be repeated in multiple unit project. Common examples of high-rise buildings, highway, pipeline engineering and residential development. The purpose of this study is to balance the time cost of repetitive project (TCTPRP) model can be calculated. Because the TCTPRP problem belongs to NP-hard (i.e., there is no algorithm solvable in polynomial time), so this paper the research can solve the problem of large scale approximation or heuristic method. Compared with the non recurring items, the complexity of repetitive project scheduling is mainly reflected in the decision variable The amount of diversification, that it may be necessary to calculate process execution mode, hiring team, logical and unit of the distribution plan. In theory, a perfect TCTPRP model or algorithm requires simultaneous processing of multiple teams, multi mode and non fixed logical order (also known as soft logic) ability. However, in the actual project and not all items can or need to hire a team, considering the multiple mode or change the logical order between the units at random. Therefore, from catering to the practical point of view, the same as the existing research to account for TCTPRP of different types of constraints. This the main research contents and results are as follows: (1) study on the TCTPRP work team in the single mode and fixed logic conditions, the goal is to determine the number of teams employ all processes and in the single best The starting time of yuan. We propose a precise model based on mixed integer linear programming, and considering the process progress assumption conditions, established the approximate model can deal with larger scale problems in a short period of time. Numerical experiments show that the model is accurate in a limited time (1 hours) the biggest problem can be resolved include 50 steps, 100 units and 10 teams; the average deviation of the calculation results of the approximate model is less than 1%, and can handle the procedure contains 100 projects in a short time. Then, we will be the exact model is extended to the non typical project (i.e., time in different units on the same process can not project), and puts forward the extended model can calculate process unit optimal allocation scheme. (2) in a single team and fixed logic is studied under the condition of multi mode TCTPRP problem, the goal is to determine the optimal execution of all processes Mode and start time in each unit. We also propose a precise model based on mixed integer linear programming, and defines two modes of elimination rules, they can effectively identify and remove infeasible or non optimal process execution mode, thereby reducing the difficulty of solving the model. For the large scale problems, we put forward the two stage of the linear programming relaxation heuristic algorithm based on the idea. Numerical experiments show that the accurate model contains 60 processes in time to deal with the biggest scale acceptable, 40 units and 20 execution modes; the average deviation of the heuristic algorithm results is less than 4% and have the ability to solve large-scale problem (. 3) multi mode soft logic TCTPRP single work team, the goal is to determine the optimal logical order between units, and all process optimal execution mode and in each unit The starting time. We analyzed the effect of soft logic may be generated for repetitive scheduling, and on this basis are presented for mixed integer nonlinear programming model to describe the problem. Considering the difficulty of solving the model, we propose a heuristic method based on genetic algorithm and linear programming. The existing literature studied just TCTPRP multi mode TCTPRP multi typical project team and single team and fixed logic problems, and they are used as a tool for solving intelligent algorithm, can not guarantee the optimality of the solutions. We work to make up for the lack of existing literature to a certain extent, and the numerical results can be used as a reference for performance evaluation the other heuristic methods.

【學(xué)位授予單位】：華北電力大學(xué)(北京)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類號(hào)】：F285

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