本文關(guān)鍵詞：混合整數(shù)非線性規(guī)劃算法及多階段隨機(jī)優(yōu)化應(yīng)用　出處：《湘潭大學(xué)》2016年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 混合整數(shù)非線性規(guī)劃 分支定界 多階段隨機(jī)規(guī)劃 條件風(fēng)險(xiǎn)值 SDDP算法

【摘要】：混合整數(shù)非線性規(guī)劃(Mixed Integer Nonlinear Programming, MINLP)以及多階段隨機(jī)規(guī)劃(Multi-stage Stochastic Programming, MSP)是優(yōu)化領(lǐng)域中較為復(fù)雜的兩類問(wèn)題,在實(shí)際生活中均有著廣泛的應(yīng)用MINLP是一類同時(shí)包含連續(xù)變量和離散變量的非線性規(guī)劃問(wèn)題,屬于整數(shù)規(guī)劃的重要分支.它具有NP-難的特性,其求解比較困難.MSP為包含不確定性因素的多步?jīng)Q策優(yōu)化問(wèn)題,由于多步?jīng)Q策的動(dòng)態(tài)性,MSP算法設(shè)計(jì)存在較大困難.另一方面,隨著社會(huì)經(jīng)濟(jì)發(fā)展,應(yīng)用領(lǐng)域中的問(wèn)題日益復(fù)雜,許多優(yōu)化建模問(wèn)題同時(shí)帶有連續(xù)變量與離散變量或者含有隨機(jī)變量.因此,如何建立兩類優(yōu)化問(wèn)題的算法研究具有重要的現(xiàn)實(shí)意義及應(yīng)用價(jià)值.本文針對(duì)兩類優(yōu)化問(wèn)題開展了如下研究：第一部分總結(jié)了求解MINLP問(wèn)題的各類基本算法及執(zhí)行算法的相應(yīng)軟件.其中算法包括五種確定型算法與一種常用啟發(fā)式算法,并對(duì)算法的設(shè)計(jì)結(jié)構(gòu)進(jìn)行了分析；然后總結(jié)開源軟件與商業(yè)軟件,對(duì)軟件的開發(fā)狀況做了詳細(xì)介紹.這些總結(jié)為MINLP的相關(guān)研究提供便利條件.第二部分針對(duì)多市場(chǎng)參與下的多時(shí)間段優(yōu)化決策問(wèn)題提出一類條件風(fēng)險(xiǎn)值(Conditional Value-at-Risk, CVaR)下的多階段隨機(jī)規(guī)劃模型.構(gòu)建了模型求解的隨機(jī)對(duì)偶動(dòng)態(tài)規(guī)劃算法(stochastic dual dynamic programming, SDDP)基于現(xiàn)代電力中新能源入網(wǎng)的很多不確定性因素,本文討論了一類多階段經(jīng)濟(jì)調(diào)度問(wèn)題.最后通過(guò)簡(jiǎn)單數(shù)值實(shí)驗(yàn)證實(shí)模型在多市場(chǎng)參與下的可應(yīng)用性.
[Abstract]:Mixed Integer Nonlinear Programming. MINLP) and multi-stage stochastic programming (MIP) and multi-stage Stochastic Programming. MSPs are two kinds of complex problems in optimization field. They are widely used in real life. MSPs are a class of nonlinear programming problems with both continuous and discrete variables. It is an important branch of integer programming. It has the characteristics of NP-hard, and its solution is difficult. MSP is a multi-step decision optimization problem with uncertain factors, because of the dynamic nature of multi-step decision. The design of MSP algorithm is difficult. On the other hand, with the development of social economy, the problems in application field are becoming more and more complex. Many optimization modeling problems have both continuous and discrete variables or random variables. How to establish algorithms for two kinds of optimization problems has important practical significance and application value. In this paper, two kinds of optimization problems are studied as follows:. The first part summarizes all kinds of basic algorithms for solving MINLP problem and the corresponding software of executing algorithm. The algorithm includes five deterministic algorithms and a common heuristic algorithm. The design structure of the algorithm is analyzed. Then summarize open source software and commercial software. The development of software is introduced in detail. These conclusions provide convenient conditions for the research of MINLP. In the second part, a class of conditional risk values are proposed for multi-time optimal decision making with multi-market participation. Conditional Value-at-Risk. A multi-stage stochastic programming model based on CVaR is presented. A stochastic dual dynamic programming algorithm for solving the model is constructed. Stochastic dual dynamic programming. SDDPs are based on a number of uncertainties associated with access to new energy sources in modern power. In this paper, a class of multi-stage economic scheduling problems is discussed. Finally, the applicability of the model under multi-market participation is verified by simple numerical experiments.
【學(xué)位授予單位】：湘潭大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：O221.2

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