A hybrid Quantum-Inspired Evolutionary Algorithm for open vehicle routing problem

This paper proposed a hybrid quantum-inspired evolutionary algorithm (HQEA) with 2-OPT sub-routes optimization for open vehicle routing problem (OVRP). In the HQEA, Quantum-Inspired Evolutionary Algorithm is used for global exploration and 2-OPT algorithm is used to optimize sub-routes for convergence acceleration. Moreover, an encoding method of converting Q-bit representation to integer representation is designed. And genetic operators of quantum crossover and quantum variation are applied to enhance exploration. The proposed HQEA is tested based on classical benchmark problems of VRP. Simulation results and comparisons with other algorithms show that the proposed HQEA has much better exploration quality and it is an effective method for OVRP.