A scheduling method in semiconductor manufacturing lines based on ant colony optimization

As is well known, the semiconductor manufacturing is one of the most complicated manufacturing processes. It can be considered as a Job shop Scheduling Problem(JSP), which is classified NP-complete problem. In this kind of problem, the combination of goals and resources can exponential increase the complexity, because a much larger searching space and more constrains exist among tasks. Ant colony optimization, as an effective meat-heuristic technique, can be adopted to find a optimized solution. In this paper, the scheduling problem of semiconductor manufacturing lines is solved by adopting ant colony optimization. The result shows that ACO performs better than some other well known algorithms and the problem can be well solved by ACO.