Multi-objective optimization model and solution for easily broken material loading based on genetic algorithms under VMI

Abstract

The material loading operation plan by artificial preparation has been unable to meet the requirements of the timely delivery when the third party logistics enterprises are involved in vendor managed inventory strategy. According to the characteristics of the easily broken material the multi-objective optimization model was established. The objective functions of this model were the vehicle loading weight utilization rate and the volume utilization rate. The five constraints were introduced. The optimal solution of the model was obtained by genetic algorithm. The solving process was introduced including the pre processing coding, the individual coding, the fitness selection and the genetic operation. The genetic algorithm program was designed by using MATLAB genetic algorithm toolbox. The easily broken material boxes loading optimization of the VMI distribution center was as an example to verify the validity of the program. Thus a whole solution which contains the optimization model and the solution procedure was provided for the easily broken material loading.