工业工程

工业工程 ›› 2016, Vol. 19 ›› Issue (3): 77-84.

• 实践与应用 • 上一篇    下一篇

智能制造系统AGV小车及缓冲区容量仿真优化

  

  1. 广东工业大学 广东省计算机集成制造系统重点实验室，广东 广州 510006
  • 出版日期:2016-06-30 发布日期:2016-08-31
  • 作者简介:陈冠中（1991-），男，广东省人，硕士研究生，主要研究方向为制造系统信息化技术.
  • 基金资助:

    国家云计算示范工程资助项目（发改办高技［2011］）2448号；国家企业互联网服务支撑软件工程技术研究中心计划资助项目（2012FU125Q09）；广东省自然科学基金资助项目（2014A030310313）

Simulation Optimization of AGV and Buffer Capacity in Intelligent Manufacturing System

  1. Key Laboratory of Computer Integrated Manufacturing System of Guangdong Province，Guangdong University of Technology，Guangzhou 510006，China
  • Online:2016-06-30 Published:2016-08-31

摘要：

具有MHS(material handling system)的智能制造系统AGV(automated guided vehicle)小车及缓冲区最大容量配置优化，属于典型的非线性整数规划问题。由于约束无法用封闭形式表达，因此较难获得问题的精确解。为此，本文提出了仿真优化的方法以获得问题的近似解。首先，对AGV小车及缓冲区最大容量配置优化问题进行了描述；其次，基于Emplant平台建立了具有MHS的智能制造系统仿真模型；然后，基于不同的优化目标，提出了3种仿真优化方法；最后，通过仿真试验对上述3种方法进行了分析与比较。分析表明，本文提出的方法及优化结果，可为企业配置AGV小车及缓冲区最大容量提供决策支持。

关键词: AGV（automated guided vehicle）容量, 缓存设置, 仿真优化

Abstract:

The maximum capacity configuration optimization of Automated Guided Vehicle (AGV) and buffer in Intelligent manufacturing system with material handling system (MHS) is a typical nonlinear integer programming problem. Because the constraints cannot be expressed in closed form, it is difficult to obtain an accurate solution to the problem. Therefore, a heuristic simulation optimization method for the approximate solution is proposed. Firstly, the AGV car and the maximum buffer capacity configuration optimization has been described. Secondly, a system simulation model is established for equipment manufacturing system with MHS, based on the Emplant platform. And then, based on different optimization goals, three heuristic simulation optimization methods are presented. Finally, the three methods are analyzed and compared through simulation. Analysis shows that the method proposed and the optimization results can provide decision support to deploy AGV car and buffer maximum capacity for enterprises.

Key words: AGV (automated guided vehicle) capacity, buffer allocation problem (BAP), simulation optimization