An Improved Quantum Ant Colony Algorithm for Fuzzy Dynamic Vehicle Routing Problem

For dynamic vehicle path problems with stochastic demand, a two-stage model is used with the objective of minimizing cost and maximizing customer satisfaction in this paper. The dynamic vehicle routing problem is converted into a static vehicle routing problem, and the quantum theory is combined with the ant colony algorithm. Quantum
$H_{\mathcal{E}}$
Gate is used to update the ant colony instead of the traditional quantum revolving gate. Using MATLAB simulation data, the quantum ant colony algorithm improved in this paper is confirmed to be one of the efficient methods to solve the problem.