Journal of System Simulation ›› 2022, Vol. 34 ›› Issue (5): 994-1002.doi: 10.16182/j.issn1004731x.joss.20-0908

• Modeling Theory and Methodology • Previous Articles     Next Articles

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

Jianlin Fu(), Guofu Ding, Jian Zhang, Haifan Jiang, Peipei Guo   

  1. School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China
  • Received:2020-11-19 Revised:2021-08-09 Online:2022-05-18 Published:2022-05-25

Abstract:

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.

Key words: automated guided vehicle(AGV), response surface methodology, discrete event simulation, NSGA-II (non-dominated sorting genetic algorithm-II)

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