本文選題：拆卸線平衡問題 + 多目標(biāo)優(yōu)化��； 參考：《西南交通大學(xué)》2014年碩士論文

【摘要】：資源短缺和環(huán)境污染是當(dāng)今社會(huì)發(fā)展面臨的兩大難題,舊產(chǎn)品回收再利用,是解決這兩大難題的有效的方法之一。當(dāng)今中國(guó)每年產(chǎn)生幾千萬件的廢舊電器,面對(duì)如此大規(guī)模廢舊產(chǎn)品的拆卸,拆卸線是最高效的組織形式。因此,對(duì)拆卸線平衡問題的研究具有重要意義。拆卸線平衡問題是一個(gè)NP問題,基于仿生原理的人工蜂群算法具有明顯的優(yōu)勢(shì)。本文研究課題結(jié)合國(guó)家自然科學(xué)基金項(xiàng)目(51205328),對(duì)拆卸線平衡問題的人工蜂群算法展開研究。標(biāo)準(zhǔn)人工蜂群算法收斂慢,易陷入局部最優(yōu)。因此,本文提出一種改進(jìn)的人工蜂群算法求解拆卸線平衡問題。 本文的改進(jìn)措施主要包括以下四個(gè)方面：(1)在生成初始解時(shí),加入任務(wù)危害和需求因素的影響,提高初始解在危害和需求方面的質(zhì)量；(2)設(shè)計(jì)一種由局部最優(yōu)解和當(dāng)前解調(diào)節(jié)的可變步長(zhǎng),加強(qiáng)對(duì)近優(yōu)解的搜索力度,加速淘汰質(zhì)量差、優(yōu)化慢的解；(3)為觀察蜂設(shè)計(jì)一種蠕動(dòng)的搜索策略,針對(duì)有危害和高需求的任務(wù)向前做微小的移動(dòng)搜索,增強(qiáng)其對(duì)后續(xù)目標(biāo)的優(yōu)化能力；(4)將嵌入衰減操作的分布估計(jì)算法引入偵察蜂的搜索策略,改進(jìn)為向較優(yōu)解中任務(wù)與位置對(duì)應(yīng)關(guān)系學(xué)習(xí)的啟發(fā)式搜索和全局隨機(jī)并用的策略,有效的改善了偵察蜂的搜索質(zhì)量。完善算法流程,設(shè)定相關(guān)參數(shù),用MATLAB將算法程序化。 用改進(jìn)的人工蜂群算法求解大量不同規(guī)模和特點(diǎn)的實(shí)例,如復(fù)雜優(yōu)先關(guān)系、多種拆卸方向、非確定拆卸時(shí)間等。并與標(biāo)準(zhǔn)人工蜂群算法和文獻(xiàn)中的一些算法進(jìn)行對(duì)比,結(jié)果表明所提算法對(duì)小規(guī)模算例均能快速找到最優(yōu)解,對(duì)大規(guī)模算例優(yōu)化結(jié)果要好于文獻(xiàn)的結(jié)果,驗(yàn)證了算法的有效性。 在本文第五章用改進(jìn)算法對(duì)某企業(yè)的實(shí)際拆卸生產(chǎn)案例進(jìn)行優(yōu)化,得到了比原方案更好的結(jié)果,提高了拆卸線的平衡率和生產(chǎn)率,充分表明了本文工作的實(shí)際意義。
[Abstract]:The shortage of resources and environmental pollution are two major problems facing the social development nowadays. The recycling and reuse of old products is one of the effective methods to solve these two problems. Tens of millions of used electrical appliances are produced every year in China. The disassembly line is the most efficient organization form in the face of the disassembly of such large scale used products. Therefore, the study of disassembly line balance is of great significance. The disassembly line balance problem is a NP problem, and the artificial bee colony algorithm based on bionic principle has obvious advantages. In this paper, the artificial bee colony algorithm for the disassembly line balance problem is studied in conjunction with the National Natural Science Foundation of China (NSFC) project No. 5120 5328. Standard artificial bee colony algorithm is easy to fall into local optimum because of its slow convergence. Therefore, an improved artificial bee colony algorithm is proposed to solve the disassembly line balance problem. The improvement measures in this paper mainly include the following four aspects: 1) when the initial solution is generated, the influence of task harm and demand factors is added. Improve the quality of the initial solution in terms of harm and demand) Design a variable step size adjusted by the local optimal solution and the current solution, strengthen the search for the near optimal solution, and accelerate the elimination of the poor quality. The slow solution 3) designed a peristaltic search strategy for observation bees, making tiny moving searches forward for hazardous and demanding tasks. In order to enhance its ability to optimize the subsequent target, the distribution estimation algorithm with embedded attenuation operation is introduced into the search strategy of the reconnaissance bee, which is improved as a heuristic search strategy to learn from the corresponding relationship between the task and the position in the optimal solution and a strategy of global random use. Effectively improves the search quality of reconnaissance bees. Improve the algorithm flow, set relevant parameters, and use MATLAB to program the algorithm. The improved artificial bee colony algorithm is used to solve a large number of examples of different scales and characteristics, such as complex precedence relations, multiple disassembly directions, uncertain disassembly time and so on. Compared with the standard artificial bee colony algorithm and some algorithms in literature, the results show that the proposed algorithm can quickly find the optimal solution for small scale examples, and the optimization results for large scale examples are better than those in literature, and the validity of the proposed algorithm is verified. In the fifth chapter, an improved algorithm is used to optimize the actual disassembly production case of an enterprise. The results are better than that of the original scheme, and the balance rate and productivity of the disassembly line are improved, which fully shows the practical significance of the work in this paper.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP18;TH186

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