本文選題：多AGV + 路徑優(yōu)化��； 參考：《陜西科技大學》2017年碩士論文

【摘要】：多AGV作業(yè)是隨著產業(yè)規(guī)模擴大、自動化程度提高、工序增多及柔性增大而逐漸得到越來越廣泛的應用。多AGV作業(yè)調度問題對提高運輸效率能夠產生一定的影響,因此對它的研究在豐富多AGV作業(yè)調度的實際應用中具有重要的意義。本文重點研究AGV在車間裝載零件過程的路徑優(yōu)化問題,多AGV在路口避碰的調度問題,建立以多AGV完成任務行駛路徑最短為目標函數(shù)的數(shù)學模型,并提出改進蟻群算法對模型進行求解。本文主要研究內容如下:(1)在研究了國內外相關文獻資料的基礎上,針對基本蟻群算法迭代收斂緩慢、易跳出全局僅在局部展開最優(yōu)解搜索等缺陷,提出一種應用局部和全局信息素同時更新的改進蟻群算法,并給出“最大最小交叉”策略,獲得信息素新的更新方案,以改善傳統(tǒng)算法的不足。(2)結合多AGV的工作流程,借助于交通流分配中交通阻抗的思想,考慮在路段和路口上產生的工作路徑和輔助路徑,分別從AGV作業(yè)調度的交通要求、運行速度的參數(shù)、行駛路徑三方面研究。分析了實驗場地中AGV行走的工作區(qū)域并將其轉化為二維結構化空間,采用柵格標識直角坐標法建立了AGV行走空間的環(huán)境地圖,為后期仿真實驗做準備。(3)針對多AGV在路口避碰的調度問題,提出了高加低減調速解決路口沖突的策略,并建立了以多AGV完成任務行駛路徑最短為目標函數(shù)的數(shù)學模型,應用上述改進蟻群算法進行求解,利用Matlab軟件對蟻群算法和改進蟻群算法進行仿真實驗,并對實驗數(shù)據(jù)對比分析,結果表明改進蟻群算法在花費較小時間成本下可以不斷溢出局部最優(yōu),能夠在全局區(qū)域內尋找新的最優(yōu)路徑,且在最優(yōu)解、平均解、最差解方面解的精度更高、性能更好。驗證了改進蟻群算法在多AGV調度優(yōu)化中的有效性,可為多AGV的實際調度作業(yè)提供參考。(4)為提高車間零件運輸?shù)淖詣踊潭?實現(xiàn)最小投入獲取最大效益的目標。本文以VB6.0為開發(fā)系統(tǒng)的平臺,SQLserver2008為后臺數(shù)據(jù)庫,借助Matlab軟件,設計開發(fā)多AGV調度管理系統(tǒng),該系統(tǒng)不僅實現(xiàn)了零件裝卸自動化管理的功能,同時利用混合編程將Matlab編寫的改進蟻群優(yōu)化算法在VB6.0中調用,給出零件裝載的先后順序,實現(xiàn)對多AGV調度管理系統(tǒng)的優(yōu)化調度和管理,提高AGV在車間工作的效率。
[Abstract]:With the expansion of industrial scale, the degree of automation, the increase of working procedure and the increase of flexibility, multiple AGV operations have been more and more widely used. The multiple AGV job scheduling problem has a certain effect on improving the transportation efficiency, so the research on it is of great significance in the practical application of multi-AGV job scheduling. In this paper, we focus on the path optimization problem of AGV loading parts in workshop, the scheduling problem of multi-AGV at intersection, and establish a mathematical model which takes the shortest path of multi-AGV to complete the task as the objective function. An improved ant colony algorithm is proposed to solve the model. The main contents of this paper are as follows: (1) on the basis of studying the relevant literature at home and abroad, the basic ant colony algorithm has some shortcomings such as slow iterative convergence, easy to jump out of the global search for the local optimal solution, etc. An improved ant colony algorithm based on local and global pheromone updating is proposed, and a "maximum and minimum crossover" strategy is given to obtain a new updating scheme of pheromone to improve the traditional algorithm. With the aid of the idea of traffic impedance in traffic flow assignment, the work path and auxiliary path generated at road sections and intersections are considered. The traffic requirements of AGV job scheduling, the parameters of running speed, and the driving path are studied respectively. The working area of AGV walking in experimental site is analyzed and transformed into two dimensional structured space. The environmental map of AGV walking space is established by using grid marking rectangular coordinate method. In order to solve the problem of collision avoidance with multiple AGV, the paper puts forward a strategy to solve the conflict of intersection with high speed increase and low speed reduction, and establishes a mathematical model which takes the shortest path to complete the task with multiple AGV as the objective function. The above improved ant colony algorithm is used to solve the problem, and the Matlab software is used to simulate the ant colony algorithm and the improved ant colony algorithm, and the experimental data are compared and analyzed. The results show that the improved ant colony algorithm can continuously overflow the local optimum and find a new optimal path in the global region, and the accuracy and performance of the improved ant colony algorithm are higher in terms of the optimal solution, the average solution and the worst solution. The effectiveness of the improved ant colony algorithm in the optimization of multiple AGV scheduling is verified. It can provide a reference for the practical scheduling of multiple AGV) to improve the automation degree of the transportation of workshop parts and to achieve the goal of obtaining the maximum benefit from the minimum input. In this paper, we use VB6.0 as the development platform and SQL Server 2008 as the backstage database, with the help of Matlab software, we design and develop the multi-AGV scheduling management system. This system not only realizes the function of automatic part handling management. At the same time, the improved ant colony optimization algorithm written by Matlab is called in VB6.0 by hybrid programming, and the sequence of parts loading is given, which realizes the optimal scheduling and management of multi-AGV scheduling management system, and improves the efficiency of AGV work in the shop floor.
【學位授予單位】：陜西科技大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP23;TB497;TP18

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