Optimization of Transport Vehicle Path Based on Quantum Evolution Algorithm

Abstract

The path optimization problem with capacity constraints has always been a combinatorial optimization problem, and the quantum evolution algorithm has excellent performance in solving combinatorial optimization problems. Firstly, after analyzing the traditional path optimization problem and the path optimization problem with capacity constraints, the distribution center is numbered 0 based on the customer-based decimal coding method, and the quantum evolution algorithm is improved according to the capacity constraint method. Fixed quantum rotation angle to dynamic rotation angle. The improved algorithm is then applied to vehicle path optimization problems with capacity constraints. Finally, through the MATLAB and LINGO methods to verify the comparison, it can be concluded that the improved quantum evolution algorithm can accurately solve the vehicle path optimization problem, and the improved quantum evolution algorithm has a good influence on the path optimization problem.