Appointment scheduling for logistics parks under truck heterogeneity and order fulfillment delay
研究了制造企业物流园区在卡车类型不同和订单延迟情况下的预约调度问题，提出加权最短加工时间优先规则和双选择遗传算法，以最小化等待、库存和加班总成本。
Appointment scheduling is critical for logistic parks of manufacturing industry firms to manage inventory turnover and schedule service objects. This work studies the appointment scheduling problem of a logistic park considering truck heterogeneity and order fulfillment delay, where the number of time windows in a day, the number of each type of appointment slot, and the service schedule in each time window are decided. The objective is to minimise the expected total cost of the truck waiting time, inventory, and overtime. We introduce a weighted shortest processing time first scheduling rule to determine the service sequence in each time window and prove that it generates optimal scheduling solutions. Based on our proposed scheduling rule, we develop a recursive calculation to formulate the cost function, which provides a tractable approach to solving combinatorially complex problems. The proposed model is solved by a dual-selection based genetic algorithm (DSGA). The performance of the DSGA is validated by comparing it to a genetic algorithm using a single tournament selection operation. Our experimental results show that the DSGA enlarges the size of subgroups with better fitness and therefore performs satisfactorily.