Solving Vehicle Routing Problem With Time Windows Based on Chaotic Adaptive Discrete Particle Swarm Optimization Algorithm

To address the limitations of existing particle swarm optimization algorithms in solving discrete problems, this paper proposes a discrete particle swarm optimization algorithm for vehicle routing problem with time windows. This algorithm enhances the velocity and position updating mechanism using an set-based strategy, making it more efficient in the discrete search process. Additionally, to further balance the algorithm’s global search and local development capabilities, this paper introduces a chaotic mapping algorithm and a nonlinear dynamic adjustment parameter strategy to enhance the algorithm’s convergence speed.