An Improved Ant Colony Algorithm is Proposed to Solve the Single Objective Flexible Job-shop Scheduling Problem

This paper takes minimizing the maximum completion time as the optimization goal, establishes a disjunctive graph model of the Job-shop scheduling problem, and proposes an improved ant colony algorithm to solve it. The new algorithm improves the ant colony algorithm from two aspects: pheromone update rules and state transition rules, aiming at the problem that ant colony algorithm is easy fall into local optimal solution and slow convergence speed. The feasibility and effectiveness of the proposed algorithm are verified by the experimental simulation of classical examples and the comparison with other relevant literature in recent years.