本文選題：供電局 + 物資倉(cāng)庫(kù)��； 參考：《華北電力大學(xué)》2017年碩士論文

【摘要】：在經(jīng)濟(jì)越來(lái)越繁榮以及用電量呈不斷上升趨勢(shì)的背景下,我國(guó)城市電網(wǎng)建設(shè)也隨之迅速的發(fā)展,對(duì)于整個(gè)城市電網(wǎng)的規(guī)劃研究而言,電網(wǎng)設(shè)施倉(cāng)庫(kù)的數(shù)目確定以及位置選擇是電網(wǎng)建設(shè)發(fā)展的重要前提。保證倉(cāng)儲(chǔ)的安全性,降低閑置物資的資源占用,對(duì)于達(dá)到物資的最佳管理,實(shí)現(xiàn)對(duì)用戶(hù)需求的準(zhǔn)時(shí)供應(yīng),保障工程生產(chǎn)以及用戶(hù)生活的順利實(shí)現(xiàn)非常重要。電網(wǎng)物資作為一種支撐電力運(yùn)行的實(shí)物載體,對(duì)于工程的建設(shè)必不可少,在人們的平常生活里也不可缺少。電網(wǎng)物資的流動(dòng)是物流的一部分,物資的流動(dòng)貫穿在整個(gè)物流網(wǎng)絡(luò)內(nèi)。物流網(wǎng)絡(luò)的規(guī)劃屬于物流體系優(yōu)化設(shè)計(jì)的戰(zhàn)略層問(wèn)題,這其中,物資倉(cāng)庫(kù)的選址是相當(dāng)重要的環(huán)節(jié)。電網(wǎng)公司進(jìn)行現(xiàn)代化物資管理、對(duì)物資做到滿(mǎn)足配送時(shí)效性的相當(dāng)重要的步驟是構(gòu)建合適的物資倉(cāng)儲(chǔ)配送體系。但是目前電網(wǎng)公司的倉(cāng)庫(kù)建設(shè)和布局存在很多不合理的地方,尚未完全達(dá)到科學(xué)的規(guī)劃。本文基于多方面的現(xiàn)場(chǎng)調(diào)研,研究電網(wǎng)企業(yè)供電局物資倉(cāng)庫(kù)布局顯現(xiàn)的主要問(wèn)題,針對(duì)電網(wǎng)公司倉(cāng)庫(kù)選址問(wèn)題,以昆明供電局為研究對(duì)象,對(duì)其進(jìn)行選址研究最終達(dá)到優(yōu)化現(xiàn)有倉(cāng)庫(kù)網(wǎng)絡(luò)布局的目的。遺傳算法是以自然界生物進(jìn)化思想為基礎(chǔ)衍生出的一種運(yùn)用廣泛的、有效的隨機(jī)搜索與優(yōu)化的算法。它最大的特征是對(duì)種群搜索策略以及在種群中每個(gè)個(gè)體之間會(huì)發(fā)生信息變換,搜索與梯度信息關(guān)聯(lián)性不大。本文通過(guò)對(duì)基本遺傳算法進(jìn)行改進(jìn)的基礎(chǔ)上,進(jìn)而利用該改進(jìn)的遺傳算法對(duì)供電局物資倉(cāng)庫(kù)的選址問(wèn)題進(jìn)行優(yōu)化處理,并且基于實(shí)際模型求解。通過(guò)實(shí)際運(yùn)用情況顯示,和常規(guī)的數(shù)學(xué)規(guī)劃方法比較而言,改進(jìn)遺傳算法運(yùn)用更為容易,同時(shí)操作的運(yùn)算速度也得以提升,尤其是對(duì)于某些規(guī)模大、情況復(fù)雜的問(wèn)題進(jìn)行處理時(shí),效果更為凸顯。所以,運(yùn)用改進(jìn)的遺傳算法來(lái)處理本文需要研究的課題,搜尋有效率的最優(yōu)解,解決供電局物資倉(cāng)庫(kù)選址。
[Abstract]:With the increasing prosperity of economy and the rising trend of electricity consumption, the construction of urban power grid in China is also developing rapidly. The determination of the number and location of power grid facilities is an important prerequisite for the development of power grid construction. It is very important to ensure the security of storage and reduce the resource occupation of idle materials in order to achieve the best management of materials, realize the punctual supply of customer demand, and ensure the smooth realization of engineering production and user life. As a kind of physical carrier to support the operation of electric power grid materials are indispensable for the construction of engineering and also indispensable in people's daily life. Power grid material flow is a part of logistics, material flow throughout the entire logistics network. The planning of logistics network belongs to the strategic layer of logistics system optimization design, among which, the location of material warehouse is a very important link. It is very important for grid company to carry out modern material management and to meet the timeliness of distribution by constructing a suitable material warehousing and distribution system. But at present, there are many unreasonable places in the warehouse construction and layout of power grid company, which has not yet reached the scientific plan. Based on a variety of field investigations, this paper studies the main problems of the distribution of material warehouse in power supply bureau of power grid, and takes Kunming power supply bureau as the research object, aiming at the location of warehouse of power grid company. Finally, the location of the warehouse network is optimized. Genetic algorithm (GA) is a widely used and effective random search and optimization algorithm derived from the idea of biological evolution in nature. The most important feature of the algorithm is the information transformation between each individual in the population and the strategy of searching for the population. The search has little correlation with the gradient information. On the basis of the improvement of the basic genetic algorithm, this paper uses the improved genetic algorithm to optimize the location problem of the material warehouse of the power supply bureau, and solves the problem based on the actual model. The actual application shows that the improved genetic algorithm is easier to use than the conventional mathematical programming method, and the speed of operation is also improved, especially for some large scale. When complex problems are dealt with, the results are even more prominent. Therefore, the improved genetic algorithm is used to deal with the problem that needs to be studied in this paper, to search for the most efficient optimal solution and to solve the material warehouse location of power supply bureau.
【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】：2017
【分類(lèi)號(hào)】：TP18;F252;F426.61

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本文編號(hào)：1856215