【摘要】：目標(biāo)函數(shù)含有區(qū)間不確定性的多目標(biāo)優(yōu)化問題廣泛存在,多目標(biāo)進(jìn)化優(yōu)化算法是解決該類問題的可行方法。當(dāng)目標(biāo)函數(shù)較多時(shí),如何有效比較區(qū)間目標(biāo)的優(yōu)劣,以獲得分布性、延展性等較好的Pareto前沿成為該類問題研究的焦點(diǎn)。現(xiàn)有研究往往采用單一的區(qū)間數(shù)大小比較方法,不能全面反映區(qū)間的信息;此外,已有方法對(duì)于進(jìn)化過程中的知識(shí)應(yīng)用不足,針對(duì)上述這些問題,本文重點(diǎn)開展了如下研究工作:(1)提出融合兩種區(qū)間數(shù)可能度排序比較策略的區(qū)間多目標(biāo)進(jìn)化優(yōu)化算法(Interval Multi-objective Evolutionary Optimization Problems Algorithm,IMOP),并用于解決實(shí)際問題。首先,論文分析了μ比較和可能度P比較兩種策略的特點(diǎn),然后,提出了基于上述兩種方法的μ"昉混合比較策略,并將該策略與NSGA-II算法框架進(jìn)行融合,給出了基于混合比較策略的區(qū)間多目標(biāo)進(jìn)化優(yōu)化算法。在數(shù)值函數(shù)中的應(yīng)用驗(yàn)證了所提方法的有效性。(2)提出了基于有向圖的改進(jìn)區(qū)間多目標(biāo)進(jìn)化優(yōu)化算法。在研究內(nèi)容(1)的基礎(chǔ)上,進(jìn)一步研究進(jìn)化過程中知識(shí)的利用,首先,基于有向圖理論給出了鄰占優(yōu)的概念,并根據(jù)該概念以及個(gè)體之間的μ"昉支配關(guān)系構(gòu)建了有向圖模型;其次,依據(jù)有向圖中形成的進(jìn)化方向?qū)β窂竭M(jìn)行延伸,以此根據(jù)種群的收斂性方向預(yù)測出優(yōu)勢個(gè)體;最終,本文將根據(jù)有向圖模型所預(yù)測出的個(gè)體與原有個(gè)體執(zhí)行交叉操作,從而起到引導(dǎo)種群進(jìn)化趨勢的作用。算法在數(shù)值函數(shù)中的應(yīng)用驗(yàn)證了算法的有效性。(3)算法在煤礦井下射頻識(shí)別(Radio Frequency Identification,RFID)閱讀器布局中的應(yīng)用。RFID技術(shù)被廣泛地應(yīng)用于井下人員的定位,并起到了令人喜悅的效果。而井下RFID系統(tǒng)閱讀器的布局直接關(guān)系射頻識(shí)別的可靠性,而煤礦井下由于環(huán)境等的影響、RFID的價(jià)格等,在考慮布局經(jīng)濟(jì)性和可靠性的前提下,使得RFID的布局具有不確定性,鑒于此,本文將上述所提方法應(yīng)用于該實(shí)際問題中。給出了煤礦井下RFID布局的多目標(biāo)不確定建模,并利用上述方法對(duì)該模型進(jìn)行求解,最后對(duì)結(jié)果進(jìn)行了對(duì)比分析。
[Abstract]:Multi-objective optimization problem with interval uncertainty exists widely in objective function, and multi-objective evolutionary optimization algorithm is a feasible method to solve this kind of problem. When there are more objective functions, how to compare the advantages and disadvantages of interval targets effectively in order to obtain better Pareto frontier such as distribution and ductility becomes the focus of this kind of research. The existing studies often use a single method to compare the number of intervals, which can not reflect the information of the interval. In addition, existing methods are inadequate for the application of knowledge in the course of evolution, and in response to these problems, The main work of this paper is as follows: (1) an interval multi-objective evolutionary optimization algorithm (Interval Multi-objective Evolutionary Optimization Problems Algorithm,IMOP) is proposed to solve the practical problems. Firstly, the paper analyzes the characteristics of 渭 comparison and possibility P comparison, then proposes a 渭 "Fang hybrid comparison strategy based on the two methods, and combines the strategy with the NSGA-II algorithm framework. An interval multiobjective evolutionary optimization algorithm based on hybrid comparison strategy is presented. The application in the numerical function proves the effectiveness of the proposed method. (2) an improved interval multi-objective evolutionary optimization algorithm based on directed graph is proposed. On the basis of research content (1), the use of knowledge in evolutionary process is further studied. Firstly, the concept of neighbor dominance is given based on directed graph theory. According to the concept and the 渭 "Fang dominating relation between individuals, a directed graph model is constructed. Secondly, the path is extended according to the evolutionary direction formed in the digraph, and the dominant individuals are predicted according to the convergence direction of the population. Finally, based on the digraph model, the individuals predicted by the digraph model will perform cross operations with the original individuals to guide the evolution trend of the population. The application of the algorithm in the numerical function verifies the validity of the algorithm. (3) the application of the algorithm in the layout of (Radio Frequency Identification,RFID reader in coal mine. RFID technology is widely used in the location of underground personnel. And it has a delightful effect. The layout of downhole RFID system reader is directly related to the reliability of RFID, while the layout of RFID is uncertain because of the influence of environment, the price of RFID and so on. In view of this, this paper applies the above method to the practical problem. The multi-objective uncertain modeling of RFID layout in coal mine is presented, and the model is solved by using the above method. Finally, the results are compared and analyzed.
【學(xué)位授予單位】：中國礦業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP18;TP391.44

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本文編號(hào)：2303617