本文關鍵詞：混合整數(shù)非線性規(guī)劃算法及多階段隨機優(yōu)化應用　出處：《湘潭大學》2016年碩士論文　論文類型：學位論文

  更多相關文章： 混合整數(shù)非線性規(guī)劃 分支定界 多階段隨機規(guī)劃 條件風險值 SDDP算法

【摘要】：混合整數(shù)非線性規(guī)劃(Mixed Integer Nonlinear Programming, MINLP)以及多階段隨機規(guī)劃(Multi-stage Stochastic Programming, MSP)是優(yōu)化領域中較為復雜的兩類問題,在實際生活中均有著廣泛的應用MINLP是一類同時包含連續(xù)變量和離散變量的非線性規(guī)劃問題,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)化問題,由于多步?jīng)Q策的動態(tài)性,MSP算法設計存在較大困難.另一方面,隨著社會經(jīng)濟發(fā)展,應用領域中的問題日益復雜,許多優(yōu)化建模問題同時帶有連續(xù)變量與離散變量或者含有隨機變量.因此,如何建立兩類優(yōu)化問題的算法研究具有重要的現(xiàn)實意義及應用價值.本文針對兩類優(yōu)化問題開展了如下研究：第一部分總結了求解MINLP問題的各類基本算法及執(zhí)行算法的相應軟件.其中算法包括五種確定型算法與一種常用啟發(fā)式算法,并對算法的設計結構進行了分析；然后總結開源軟件與商業(yè)軟件,對軟件的開發(fā)狀況做了詳細介紹.這些總結為MINLP的相關研究提供便利條件.第二部分針對多市場參與下的多時間段優(yōu)化決策問題提出一類條件風險值(Conditional Value-at-Risk, CVaR)下的多階段隨機規(guī)劃模型.構建了模型求解的隨機對偶動態(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)濟調度問題.最后通過簡單數(shù)值實驗證實模型在多市場參與下的可應用性.
[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.
【學位授予單位】：湘潭大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：O221.2

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