【摘要】：隨著科技的發(fā)展,人們的生活水平不斷提高,機(jī)電產(chǎn)品的更新?lián)Q代也越來越快,報(bào)廢處理問題隨之而來,對報(bào)廢產(chǎn)品進(jìn)行回收不僅可以保護(hù)環(huán)境,還能節(jié)省資源。而拆卸是回收的前提,用合適的拆卸方案對廢棄的機(jī)電產(chǎn)品進(jìn)行拆卸,能提高拆卸效率,提升拆卸收益。拆卸序列規(guī)劃是拆卸問題中的重要內(nèi)容,拆卸序列規(guī)劃問題在數(shù)學(xué)上屬于NP-完全型,即隨著產(chǎn)品復(fù)雜度的提高,對產(chǎn)品拆卸過程進(jìn)行規(guī)劃將變得異常復(fù)雜和困難。本研究針對復(fù)雜機(jī)電產(chǎn)品拆卸序列規(guī)劃問題,利用智能優(yōu)化算法進(jìn)行求解,提高產(chǎn)品的拆卸效率。本文的主要研究內(nèi)容包括以下四個(gè)方面:(1)本文首先介紹了拆卸的概念和類型、產(chǎn)品的拆卸信息、拆卸信息模型的分類等內(nèi)容,在分析已有模型的基礎(chǔ)上,對常規(guī)的拆卸信息模型進(jìn)行改進(jìn),將拆卸對象、拆卸方向、約束類型、拆卸工具、拆卸成本等信息進(jìn)行處理加入到改進(jìn)后的拆卸信息模型中,極大的豐富了產(chǎn)品的拆卸信息。并對這些信息進(jìn)行了數(shù)字化處理,以便于計(jì)算機(jī)程序讀取,為接下來利用智能算法對拆卸序列的求解和優(yōu)化打下基礎(chǔ)。(2)介紹了智能優(yōu)化算法的特點(diǎn),具體介紹了蟻群算法的原理、數(shù)學(xué)模型,針對基本蟻群算法的不足,增加了螞蟻路徑的約束,改變了信息素更新機(jī)制,提出以拆卸優(yōu)先約束矩陣為基礎(chǔ)的改進(jìn)蟻群算法,并使用MATLAB進(jìn)行編碼,以某型號洗衣機(jī)為例進(jìn)行了驗(yàn)證。試?yán)Y(jié)果證明了改進(jìn)蟻群算法的可行性。(3)介紹了標(biāo)準(zhǔn)遺傳算法的原理和數(shù)學(xué)模型以及在拆卸序列規(guī)劃方面的研究和應(yīng)用,并針對其在早熟收斂和局部搜索方面的不足,對遺傳算法的基因組編碼方式、遺傳算子和一般流程進(jìn)行了改進(jìn),提出了基于拆卸優(yōu)先約束矩陣的自適應(yīng)遺傳算法,并針對某型號洗衣機(jī)實(shí)例,使用MATLAB進(jìn)行算法的具體編碼和計(jì)算,取得了良好的結(jié)果,證明了該改進(jìn)算法的可行性和有效性;并對蟻群算法和遺傳算法改進(jìn)前后的優(yōu)化結(jié)果進(jìn)行分析比較。(4)針對拆卸方案的評價(jià)問題,提出了基于理想度公式的多指標(biāo)評價(jià)體系,綜合考慮產(chǎn)品拆卸時(shí)的技術(shù)性、經(jīng)濟(jì)性、環(huán)境性等影響,建立拆卸序列評價(jià)指標(biāo)體系。在用智能算法進(jìn)行產(chǎn)品的拆卸過程規(guī)劃的基礎(chǔ)上,針對搜索到的少數(shù)幾條可行拆卸序列進(jìn)行分析,并進(jìn)行多指標(biāo)綜合評價(jià),從而得到綜合指標(biāo)優(yōu)化的拆卸序列。為拆卸序列的評價(jià)問題提供了一種可行、有效的方法。
[Abstract]:With the development of science and technology, people's living standard is improving, and the upgrading of mechanical and electrical products is also faster and faster. The problem of disposal of end-of-life follows. Recycling of end-of-life products can not only protect the environment, but also save resources. Disassembly is the premise of recycling. Disassembly of discarded mechanical and electrical products with suitable disassembly scheme can improve the disassembly efficiency and increase the disassembly income. Disassembly sequence planning is an important part of disassembly problem. The disassembly sequence planning problem belongs to the complete type of NP- mathematically, that is, with the increase of product complexity, the planning of product disassembly process will become extremely complex and difficult. In order to improve the disassembly efficiency, intelligent optimization algorithm is used to solve the disassembly sequence planning problem of complex electromechanical products. The main contents of this paper include the following four aspects: (1) this paper first introduces the concept and type of disassembly, the disassembly information of products, the classification of disassembly information model, etc. The conventional disassembly information model is improved, and the information of disassembly object, disassembly direction, constraint type, disassembly tool and disassembly cost are added to the improved disassembly information model, which greatly enriches the disassembly information of the product. The information is digitally processed in order to facilitate the computer program to read, which lays the foundation for the solution and optimization of the disassembly sequence by using the intelligent algorithm. (2) the characteristics of the intelligent optimization algorithm are introduced. The principle and mathematical model of ant colony algorithm are introduced in detail. Aiming at the deficiency of basic ant colony algorithm, the constraints of ant path are added, the pheromone updating mechanism is changed, and an improved ant colony algorithm based on disassembly priority constraint matrix is proposed. MATLAB is used to code, and a washing machine is used as an example to verify. The results of an example show that the improved ant colony algorithm is feasible. (3) the principle and mathematical model of standard genetic algorithm and its research and application in disassembly sequence planning are introduced, and its shortcomings in premature convergence and local search are also discussed. An adaptive genetic algorithm based on disassembly priority constraint matrix is proposed to improve the genetic algorithm, genetic operator and general flow chart of genetic algorithm, and an example of a washing machine is given. MATLAB is used to code and calculate the algorithm, and good results are obtained, which proves the feasibility and effectiveness of the improved algorithm. The optimization results before and after the improvement of ant colony algorithm and genetic algorithm are analyzed and compared. (4) aiming at the evaluation problem of disassembly scheme, a multi-index evaluation system based on ideal degree formula is proposed. The evaluation index system of disassembly sequence was established. On the basis of planning the disassembly process of the product with intelligent algorithm, the paper analyzes a few feasible disassembly sequences which are searched, and evaluates the disassembly sequence with multiple indexes, and then obtains the disassembly sequence optimized by the synthetic index. It provides a feasible and effective method for evaluating disassembly sequence.
【學(xué)位授予單位】：內(nèi)蒙古工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：X705;TP18

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本文編號：2292835