A Study of Job-shop Scheduling Problem Based on Improved Ant Colony Algorithm and Its Simulations

Ant colony algorithm has the characteristics of good positive feedback,robustness and parallel groups,and is an optimized algorithm for simulating ants' swarm intelligence behavior.This paper proposed an advanced ant colony algorithm for overcomeing the defect that the basic ant colony algorithm is easy to fall into the local convergence.This proposed method adopted a new state transition rule.The pheromone update strategy would be adjusted when the algorithm falls into the local convergence.And the coefficient and intensity of pheromone volatile would be adjusted dynamically according to the degree of local convergence.This algorithm can quickly jump out of the local convergence and obtain a global optimal solution.The simulation demonstrates the validity of the proposed algorithm for Job Shop Scheduling problem.