本文關(guān)鍵詞： 水資源管理 優(yōu)化模型 區(qū)間參數(shù) 機(jī)會(huì)約束 隨機(jī)分析 水環(huán)境容量　出處：《華北電力大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：由于工業(yè)社會(huì)活動(dòng)的影響,區(qū)域水資源問(wèn)題成為人們關(guān)注的課題,給社會(huì)環(huán)境的協(xié)調(diào)可持續(xù)發(fā)展帶來(lái)嚴(yán)峻的挑戰(zhàn),所以,開(kāi)展區(qū)域水資源規(guī)劃對(duì)現(xiàn)代區(qū)域社會(huì)經(jīng)濟(jì)發(fā)展起著至關(guān)重要的作用。然則,水資源系統(tǒng)本身特有的不確定性、參數(shù)之間互動(dòng)關(guān)系復(fù)雜,對(duì)傳統(tǒng)的確定性優(yōu)化理論是很大的挑戰(zhàn)。因此,本文研究目的便是把不確定規(guī)劃方法運(yùn)用到水資源系統(tǒng)優(yōu)化中來(lái)處理這種不確定性和復(fù)雜性。在本文中,針對(duì)濱州市高新區(qū)在發(fā)展過(guò)程中所要面對(duì)的水資源短缺及水環(huán)境污染的問(wèn)題,在蒙特卡洛模擬(MonteCarlo)技術(shù)的基礎(chǔ)上,首先創(chuàng)建了不確定區(qū)間-機(jī)會(huì)約束線性優(yōu)化模型(ICCP)和。結(jié)果表明,ICCP可以很好地反映系統(tǒng)的復(fù)雜性和不確定性,得到不同環(huán)境風(fēng)險(xiǎn)水平下的決策方案,幫助決策者權(quán)衡水環(huán)境風(fēng)險(xiǎn)與區(qū)域經(jīng)濟(jì)之間的關(guān)系,為相關(guān)部門(mén)制定合理的經(jīng)濟(jì)、環(huán)境與社會(huì)可持續(xù)發(fā)展戰(zhàn)略規(guī)劃提供理論與技術(shù)支持。現(xiàn)實(shí)中首先確定各行業(yè)供水量的目標(biāo)值,各行業(yè)根據(jù)該目標(biāo)值制定未來(lái)的發(fā)展規(guī)模,但是,水資源分配不一定都能夠按照計(jì)劃進(jìn)行,受諸多因素的影響有時(shí)候會(huì)得不到足夠的分配量,此時(shí)面臨一個(gè)不能夠滿足需要的懲罰,ICCP對(duì)此是無(wú)能為力的,若水量是已知分布的隨機(jī)變量,兩階段優(yōu)化模型(TSP)能夠很好地解決此問(wèn)題。因此,基于對(duì)ICCP模型結(jié)果的分析以及模型存在的問(wèn)題,構(gòu)建了基于水環(huán)境容量的兩階段隨機(jī)水資源優(yōu)化模型(ICCTSP)。在兩階段(TSP)中,第一階段：在隨機(jī)事件發(fā)生之前,根據(jù)經(jīng)驗(yàn)制定一個(gè)決策；第二階段：當(dāng)隨機(jī)事件發(fā)生之后,考慮到會(huì)引起的懲罰,修正之前制定的經(jīng)驗(yàn)性決策,重新尋求使得系統(tǒng)最優(yōu)化的決策。ICCTSP能更好的處理水量的隨機(jī)性問(wèn)題,其結(jié)合了更多的不確定理論,能夠處理多重不確定性問(wèn)題,多種不確定性理論的結(jié)合是未來(lái)不確定性優(yōu)化的發(fā)展方向。
[Abstract]:Due to the influence of industrial social activities, regional water resources problem has become a topic of concern to people, which brings severe challenges to the coordinated and sustainable development of the social environment. The development of regional water resources planning plays an important role in the development of modern regional society and economy. However, the uncertainty of water resources system itself and the interaction between parameters are complex. It is a great challenge to the traditional deterministic optimization theory. Therefore, the purpose of this paper is to apply the uncertain programming method to the optimization of water resources system to deal with the uncertainty and complexity. In view of the problems of water resources shortage and water environment pollution in the development of Binzhou High-tech Zone, based on Monte Carlo simulation technology. Firstly, the uncertain interval-opportunity constrained linear optimization model (ICCPP) and the results show that the ICCP can well reflect the complexity and uncertainty of the system. The decision scheme under different environmental risk levels is obtained to help decision makers to balance the relationship between water environmental risk and regional economy, and to formulate a reasonable economy for relevant departments. The strategic planning of environmental and social sustainable development provides theoretical and technical support. In reality, the target value of water supply for each industry is first determined, and the future development scale of each industry is determined according to the target value, however. The allocation of water resources may not always be carried out according to the plan, and sometimes the allocation will not be sufficient due to many factors. At this time, faced with a punishment that cannot meet the needs, ICCP is powerless to do so. If the water quantity is a random variable of known distribution, the two-stage optimization model can solve this problem very well. Therefore, based on the analysis of the results of the ICCP model and the problems existing in the model. A two-stage stochastic water resources optimization model based on the water environment capacity is constructed. In the two-stage TSPs, the first stage: before the random events occur, a decision is made according to the experience; The second stage: when random events occur, take into account the penalties that will be caused, and revise the previous empirical decisions. It can deal with the stochastic problem of water quantity better, which combines more uncertainty theory, and can deal with multiple uncertainty problems. The combination of uncertainty theory is the development direction of uncertainty optimization in the future.
【學(xué)位授予單位】：華北電力大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TV213.4

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