【摘要】：隨著我國(guó)制造業(yè)的不斷發(fā)展,越來(lái)越多的報(bào)廢機(jī)電產(chǎn)品帶來(lái)的資源再利用問(wèn)題與潛藏的環(huán)境污染問(wèn)題亟待解決,而拆卸是解決這一系列問(wèn)題的基礎(chǔ)與關(guān)鍵。如何對(duì)廢舊機(jī)電產(chǎn)品進(jìn)行高效的拆卸利用已經(jīng)是現(xiàn)今“綠色技術(shù)”的研究熱點(diǎn),也是機(jī)電產(chǎn)品生命周期研究中所面臨的重要課題。因此,本文致力于探索更為高效的拆卸分析及序列規(guī)劃方法,以改進(jìn)人工蜂群算法為基礎(chǔ),對(duì)復(fù)雜機(jī)電產(chǎn)品的并行拆卸序列規(guī)劃方法進(jìn)行了研究。首先,對(duì)復(fù)雜產(chǎn)品的拆卸信息模型及評(píng)價(jià)指標(biāo)進(jìn)行了探討,為后續(xù)拆卸序列規(guī)劃的研究奠定了基礎(chǔ)。其次,針對(duì)拆卸序列規(guī)劃易出現(xiàn)的組合爆炸問(wèn)題,提出了基于人工蜂群算法的解決方案。同時(shí),針對(duì)此算法的不足之處,提出了基于二叉樹(shù)的優(yōu)先約束策略,對(duì)算法中隨機(jī)生成的初始種群進(jìn)行約束化處理,使之能夠有效提取拆卸解空間信息;定義了可行度算法與適應(yīng)度算法協(xié)同搜尋蜜源,在保證種群多樣性的前提下提高了改進(jìn)算法的收斂速度,使之更加適合求解拆卸序列規(guī)劃問(wèn)題。最后,通過(guò)實(shí)例計(jì)算并與其他算法進(jìn)行對(duì)比,證明了本文所述改進(jìn)算法的可行性及高效性。在此改進(jìn)算法的基礎(chǔ)上,本文提出了一種適應(yīng)于復(fù)雜機(jī)電產(chǎn)品的并行拆卸序列規(guī)劃方法。通過(guò)對(duì)比分析并行拆卸與傳統(tǒng)串行拆卸的不同之處,就并行拆卸的關(guān)鍵問(wèn)題提出了相應(yīng)的解決方案:定義了可變序列矩陣方法,由此提出了一種單一集合的并行化分析方法,用以解決并行拆卸序列長(zhǎng)度與每步步長(zhǎng)不確定的問(wèn)題,建立了串、并行拆卸序列分析之間的聯(lián)系紐帶;針對(duì)并行拆卸繁多的單元選取情況,提出誘導(dǎo)因子方法,引領(lǐng)規(guī)劃過(guò)程向最優(yōu)方向進(jìn)行演化。最后,于改進(jìn)人工蜂算法的基礎(chǔ)上,對(duì)某發(fā)動(dòng)機(jī)模型進(jìn)行并行拆卸序列規(guī)劃求解,證明了本文所述基于改進(jìn)算法的并行拆卸方法的優(yōu)越性。
[Abstract]:With the continuous development of manufacturing industry in China, more and more problems of resource reuse and latent environmental pollution caused by end-of-life mechanical and electrical products need to be solved, and disassembly is the basis and key to solve these problems. How to disassemble and utilize the waste electromechanical products efficiently has become the research hotspot of "green technology" nowadays, and it is also an important subject in the research of the life cycle of electromechanical products. Therefore, this paper is devoted to exploring more efficient disassembly analysis and sequence planning methods. Based on the improved artificial bee colony algorithm, the parallel disassembly sequence planning method for complex electromechanical products is studied. Firstly, the disassembly information model and evaluation index of complex products are discussed, which lays a foundation for the research of disassembly sequence planning. Secondly, a solution based on artificial bee colony algorithm is proposed to solve the combinatorial explosion problem which is easy to occur in disassembly sequence planning. At the same time, aiming at the shortcomings of the algorithm, a priority constraint strategy based on binary tree is proposed. The initial population generated randomly in the algorithm is constrained to extract the information of disassembly solution space effectively. The feasibility algorithm and fitness algorithm are defined to search honey source in cooperation. The convergence speed of the improved algorithm is improved on the premise of ensuring diversity of population, which makes it more suitable for solving disassembly sequence planning problem. Finally, the feasibility and efficiency of the improved algorithm are proved by example calculation and comparison with other algorithms. Based on the improved algorithm, a parallel disassembly sequence planning method for complex electromechanical products is proposed. By comparing and analyzing the differences between parallel disassembly and traditional serial disassembly, the corresponding solutions to the key problems of parallel disassembly are put forward: the variable sequence matrix method is defined, and a single set parallelization analysis method is proposed. In order to solve the problem that the length of parallel disassembly sequence and the length of each step are uncertain, the link between serial disassembly sequence analysis and parallel disassembly sequence analysis is established. Leading the planning process to the optimal direction of evolution. Finally, on the basis of the improved human worker bee algorithm, the parallel disassembly sequence planning of an engine model is carried out, which proves the superiority of the parallel disassembly method based on the improved algorithm in this paper.
【學(xué)位授予單位】：合肥工業(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;X705

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