A genetic algorithm for dynamic advanced planning and scheduling (DAPS) with a frozen interval

This paper investigates a dynamic advanced planning and scheduling (DAPS) problem where new orders arrive on a continuous basis. A periodic policy with a frozen interval is adopted to increase stability on the shop floor. A genetic algorithm is developed to find a schedule such that both production idle time and penalties on tardiness and earliness of both original orders and new orders are minimized at each rescheduling point. The proposed methodology is tested on a series of examples. A representative example is illustrated to indicate that the suggested approach can improve the schedule stability while retaining efficiency.