An intelligent anytime scheduling method for robotic cellular manufacturing systems

The work proposes a hybrid search for solving the scheduling problem in robotic cellular manufacturing systems. The proposed approach utilizes a combination of the A∗ approach with a depth-first search to iteratively explore the reachability graph of a place-timed Petri net to obtain transition firing sequences that lead from an original state to a final one. This approach can effectively produce near-optimal solutions within a short computational time, while continuously improving the solution quality as more time is allocated for the search. Experimental evaluations of some example systems have demonstrated the efficacy of the approach.