【摘要】：隨著社會(huì)競(jìng)爭(zhēng)日益激烈,越來(lái)越多的企業(yè)改粗放型生產(chǎn)方式為集約型生產(chǎn)方式,大量采用先進(jìn)生產(chǎn)設(shè)備。設(shè)備布局作為企業(yè)規(guī)劃的重要部分之一也越來(lái)越受到制造業(yè)的重視。本文以工廠生產(chǎn)車(chē)間設(shè)備布局為研究對(duì)象,分析設(shè)備布局研究現(xiàn)狀、設(shè)備布局特點(diǎn),研究以設(shè)備占地面積和多個(gè)生產(chǎn)階段里設(shè)備之間總物流成本為優(yōu)化目標(biāo)的魯棒雙行設(shè)備布局方法。 目前學(xué)者研究多行和單行設(shè)備布局偏多,對(duì)于雙行設(shè)備布局研究甚少,而實(shí)際工廠中雙行布局也具有很大實(shí)際意義。考慮到問(wèn)題的特殊性,本文著眼于雙行設(shè)備布局問(wèn)題。另外,很多前人學(xué)者的文獻(xiàn)大多基于單生產(chǎn)階段的布局問(wèn)題研究。隨著實(shí)際生產(chǎn)線的需要,物流量往往隨著不同的生產(chǎn)階段變化。當(dāng)設(shè)備布局改變時(shí),企業(yè)其實(shí)更關(guān)心在多個(gè)階段里的最后布局總開(kāi)銷(xiāo)。靜態(tài)布局往往不能適應(yīng)市場(chǎng)需求,而動(dòng)態(tài)布局又存在重置布局的成本問(wèn)題,因此本文將多個(gè)生產(chǎn)階段納入研究且采用魯棒設(shè)備布局。 針對(duì)魯棒雙行設(shè)備布局問(wèn)題,本文提出一種基于分解的多目標(biāo)進(jìn)化算法(MOEA/D算法)的求解方法,主要做了如下幾方面的工作：1)采用Pareto最優(yōu)解方法,優(yōu)化魯棒雙行設(shè)備布局問(wèn)題中的多階段總物流成本和設(shè)備占地面積兩個(gè)優(yōu)化目標(biāo)。2)采用帶擁擠度算法的MOEA/D算法用于求解魯棒雙行設(shè)備布局問(wèn)題中的連續(xù)問(wèn)題。3)采用切比雪夫分解法將多目標(biāo)問(wèn)題分解成一系列子問(wèn)題進(jìn)行優(yōu)化。4)魯棒雙行設(shè)備布局問(wèn)題同時(shí)包含離散問(wèn)題和連續(xù)問(wèn)題,本文研究了MOEA/D算法同時(shí)求解這兩個(gè)問(wèn)題以及單步求解這兩個(gè)問(wèn)題時(shí)的區(qū)別。5)小規(guī)模問(wèn)題通過(guò)與CPLEX對(duì)比研究MOEA/D的有效性,大規(guī)模問(wèn)題通過(guò)實(shí)驗(yàn)結(jié)果分析算法的穩(wěn)定性和有效性。 通過(guò)研究本文得出MOEA/D算法在求解魯棒雙行設(shè)備布局問(wèn)題時(shí)具有效性、準(zhǔn)確性和穩(wěn)定性。
[Abstract]:With the increasingly fierce social competition, more and more enterprises change the extensive mode of production to intensive mode of production, and adopt a large number of advanced production equipment. As an important part of enterprise planning, equipment layout is paid more and more attention by manufacturing industry. In this paper, the factory workshop equipment layout as the research object, analysis of the status quo of equipment layout, equipment layout characteristics, In this paper, a robust two-row equipment layout method is studied, in which the equipment covers an area and the total logistics cost between the equipments in multiple production stages is taken as the optimization objective. At present, many scholars study the layout of multi-row and single-row equipment, but there is little research on the layout of two-row equipment, and the dual-row layout in the actual factory is of great practical significance. Considering the particularity of the problem, this paper focuses on the layout of two-line equipment. In addition, many previous scholars mostly based on the single-stage layout of the study. With the demand of the actual production line, the material flow often changes with different production stages. When the device layout changes, the enterprise is actually more concerned with the final layout overhead in multiple phases. Static layout is often unable to meet the market demand, and dynamic layout has the cost of resetting layout. Therefore, in this paper, multiple production stages are included in the study and robust equipment layout is adopted. In this paper, a decomposition based multi-objective evolutionary algorithm (MOEA/D) is proposed to solve the robust two-row device layout problem. The main works are as follows: 1) the Pareto optimal solution method is adopted. There are two optimization objectives in the robust two-row equipment layout problem: the total logistics cost of multi-stage and the space occupied by the equipment. 2) the MOEA/D algorithm with congestion algorithm is used to solve the continuous problem in the robust two-row equipment layout problem. 3) the continuous problem in the robust two-row equipment layout problem is solved by using the MOEA/D algorithm with congestion algorithm. The method of Chebyshev decomposition is used to decompose the multi-objective problem into a series of sub-problems. 4) the robust two-row layout problem includes both discrete and continuous problems. In this paper, we study the difference of MOEA/D algorithm in solving these two problems simultaneously and in one step. 5) small scale problems are compared with CPLEX to study the effectiveness of MOEA/D, and large scale problems are analyzed by experimental results to analyze the stability and effectiveness of the algorithm. By studying the MOEA/D algorithm, it is concluded that the algorithm is effective, accurate and stable in solving the robust two-line device layout problem.
【學(xué)位授予單位】：北京郵電大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TP18

【參考文獻(xiàn)】

相關(guān)期刊論文 前9條

1 李英娜,李建勇,李志輝;柔性制造系統(tǒng)魯棒性設(shè)備布局研究[J];北方交通大學(xué)學(xué)報(bào);2001年04期

2 陳皓;崔杜武;嚴(yán)太山;李凌波;;基于競(jìng)爭(zhēng)指數(shù)的模擬退火排序選擇算子[J];電子學(xué)報(bào);2009年03期

3 黃衛(wèi)華;許小勇;范建坤;;實(shí)數(shù)編碼遺傳算法中常用變異算子的Matlab實(shí)現(xiàn)及應(yīng)用[J];廣西輕工業(yè);2007年01期

4 郝國(guó)生;嚴(yán)玉若;黃永青;胡培亮;章磊;路娟;季君;;基于三角函數(shù)的遺傳算法選擇算子[J];江南大學(xué)學(xué)報(bào)(自然科學(xué)版);2010年02期

5 文詩(shī)華;鄭金華;李密青;;多目標(biāo)進(jìn)化算法中變異算子的比較與研究[J];計(jì)算機(jī)工程與應(yīng)用;2009年02期

6 鄭向偉;劉弘;;多目標(biāo)進(jìn)化算法研究進(jìn)展[J];計(jì)算機(jī)科學(xué);2007年07期

7 劉瓊;許金輝;張超勇;;基于改進(jìn)蛙跳算法的魯棒性車(chē)間布局[J];計(jì)算機(jī)集成制造系統(tǒng);2014年08期

8 公茂果;焦李成;楊咚咚;馬文萍;;進(jìn)化多目標(biāo)優(yōu)化算法研究[J];軟件學(xué)報(bào);2009年02期

9 李晨;寧紅云;;改進(jìn)的遺傳算法選擇算子[J];天津理工大學(xué)學(xué)報(bào);2008年06期

，

本文編號(hào)：2276723