基于响应面和NSGA-Ⅱ的AGV系统多目标优化配置  

Multi-Objective Optimization Configuration of AGV System Based on Response Surface and NSGA-Ⅱ

作　　者：付建林[1] 丁国富[1] 张剑[1] 江海凡 郭沛佩 Fu Jianlin;Ding Guofu;Zhang Jian;Jiang Haifan;Guo Peipei(School of Mechanical Engineering,Southwest Jiaotong University,Chengdu 610031,China)

机构地区：[1]西南交通大学机械工程学院,四川成都610031

出　　处：《系统仿真学报》2022年第5期994-1002,共9页Journal of System Simulation

基　　金：四川省重大科技专项(2020YJ0215)。

摘　　要：AGV(automated guided vehicle)系统对于制造系统的生产柔性和生产效率具有重要作用,由于AGV系统具有许多的变量且有动态性、随机性特点,其优化配置比较复杂。提出了一种将系统仿真、数学解析和多目标优化相结合的方法,对AGV系统进行了优化配置;运用离散事件仿真模拟AGV系统运行,利用敏感性分析分离设计变量,采用析因试验和响应面方法拟合多目标优化数学模型,基于非支配解排序多目标遗传算法求解多目标优化解。通过AGV系统实例,证明了该方法的有效性,可为制造系统和物流仓储领域中AGV系统的优化配置提供一种有效的系统性分析方法。Automated guided vehicle(AGV)system plays an important role in the production flexibility and efficiency in manufacturing systems.Due to the dynamic and stochastic characteristics of AGV system with many variables,its optimal configuration is relatively complex.A method combining system simulation,mathematical analysis and multi-objective optimization is proposed to optimize the configuration of AGV system.The discrete event simulation is used to simulate the operation of AGV system,the sensitivity analysis is used to separate design variables,the factorial experiments and response surface methods are used to build the fitting multi-objective optimization mathematical model,and the non-dominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ)is used to solve the multi-objective optimization problem.The effectiveness of the method is proved by an industrial case study,which provides an effective systematic analysis method for the optimal configuration of AGV system in manufacturing or logistics systems.

关 键 词：AGV 响应面 离散事件仿真 非支配解排序多目标遗传算法 

分 类 号：TH166[机械工程—机械制造及自动化] TP391[自动化与计算机技术—计算机应用技术]