A Fusion Algorithm Based on Physarum Polycephalum Network and Ant Colony optimization Algorithm

Abstract

Based on experimental analysis, it is known that physarum polycephalum shows a physiological bias towards the “important feeding channel A fusion algorithm named Physarum-Network ant colony optimization algorithm (PNACO) is proposed by combining the mechanisms with the original ant colony algorithm. The algorithm takes the advantages of ant colonies and slime molds on the update of the pheromone matrix, which increases the selection probability of the “optimal path” and improves the convergence speed and robustness. A multi-AGV path planning strategy based on the PNACO algorithm is proposed and a workshop logistics system is taken as an example to verify the feasibility and robustness of the strategy.

Publication
2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)