Based on two element neighborhood search quantum genetic algorithm to solve the vehicle scheduling problem

Abstract

Aiming at the real time distribution problem in logistics distribution that was vehicle routing problem with capacity constraints. An adaptive quantum genetic algorithm is proposed to minimize the traffic path. The idea of “adaptive genetic algorithm” is used for reference and a new quantum rotation angle updating strategy is proposed. And the direction of the change of the quantum rotation gate is guided by the change of fitness value to improve the depth of the global search algorithm. A mutation operation is designed to keep the population diversity of adaptive quantum genetic algorithm, and then to improve the width of the global search. The local development ability of the algorithm is enhanced by introducing 2-optimization local search algorithm. The effectiveness and superiority of the proposed algorithm are verified by simulation experiment and algorithm comparison.