Aiming at vehicle routing problem and combining the advantages of ant colony and particle swarm optimization, an intelligent optimization algorithm of adaptive ant colony and particle swarm optimization is proposed. Through the simulation of ant colony and bird swarm intelligence mechanism, the particle swarm algorithm and the ant colony algorithm heuristic strategy are combined, and different search strategies are used in different stages of the algorithm. The adaptive adjustment is adopted, and the feedback information is obtained by dynamic interaction with the environment, thus speeding up the convergence speed, improving the learning ability, avoiding the local optimum, getting the best solution and improving the efficiency. The simulation experiment shows that the algorithm has fast convergence speed, strong optimization ability, and can obtain better optimization results. It has some advantages in solving vehicle routing problem.
Research on Vehicle Routing Planning Based on Adaptive Ant Colony and Particle Swarm Optimization Algorithm
Int. J. ITS Res.
International Journal of Intelligent Transportation Systems Research ; 19 , 1 ; 83-91
2021-04-01
9 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Adaptive , Ant colony , Particle swarm optimization , Hybrid optimization algorithm , Vehicle routing problem Engineering , Electrical Engineering , Automotive Engineering , Robotics and Automation , Computer Imaging, Vision, Pattern Recognition and Graphics , Civil Engineering , User Interfaces and Human Computer Interaction
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