The Multi-objective Design Optimization of Automated Guided Vehicles Car Structure using Genetic Algorithms

Abstract

This paper aims to the new design method of automated guided vehicles (AGV) car structure. To obtain the optimum design, the multi-objective genetic algorithm (MOGA) such as NSGA-II combined with Finite Element method (FEM) was developed to analyze the structure and to search the minimum mass and structural stress as two objective functions subject to two structural constraints, including with structural buckling and defection. Finally, the results of nondominated solutions were represented because of the trade-off between the structural mass and stress. This paper shows that it is possible to use NSGA-II combined with FEM to solve the optimum design of the AGV car structure as a multi-objective optimization problem.