A heuristic search approach using approximate solutions to Petri net state equations for scheduling flexible manufacturing systems

This paper proposes a new heuristic search approach based on analytic theory of the Petri net state equations for scheduling flexible manufacturing systems (FMSs) with the goal of minimizing makespan. The proposed method models an FMS using a timed Petri net and exploits approximate solutions of the net's state equation to predict the total cost (makespan) from the initial state through the current state to the goal. That is, the heuristic function considers global information provided by the state equation. This makes the method able to obtain solutions better than those obtained using prior works that consider only the current status or limited global information. In addition, to reduce memory requirement and thus to increase the efficiency of handling larger systems, the proposed scheduling algorithm contains a procedure to reduce the searched state space.