Optimization of Ship Field Repair Scheduling Based on Depth First Search Method

Abstract

Ship field repair sheduling is a asynchronism and concurrency process. Although it is complex, it is very important in the field repair decision at wartime. Through the optimal field repair scheduling, we can reduce the total repair time and improve repair efficiency. Regretly ship field repair scheduling optimization model has not been researched perfectly. Generally speaking, there are field repair processes of two kinds. Repair processe of one kind is that the repair sequence is fixed and the repair resource need not be scheduled. It is used to schedule repair tasks of the same kind. Repair processe of the other kind is that the repair resoure should be scheduled to reduce the total repair time. It is used to schedule the repair tasks of the different kind. The scheduling method of the first kind has been researched in math work. But the math model turns to be complex when the amount of the object increases. The scheduling method of the second kind is more complex than the first one. It is a typical asynchronism and concurrency process. So the new feasible models should be researched. Based on the repair processes of the two kinds, two ship field repair scheduling models are founded based on timed colored Petri net (TCPN) and depth first search method in this paper. The timed colored Petri net is used to model repair process and its transition rules are used to design the arithmetic. The arithmetics of the two models are explained in detail. In the second arithmetic, the conflict-solution is researched particularly. Conflict-solution method is corresponding to the field repair resource scheduling plan. The conflict-solution problem is solved based on depth first search method of artifical intelligence. Through the examples of the use of the two arithmetics, we find that the arithmetics given in this paper are very feasible and convenient. The field repair scheduling optimization models are the basic of the ship field repair and safety recovery intelligent decision support system. Through the optimization models we can generate the repair scheduling plan intelligently. That is to say the two models are not only optimization models but also intelligent models.