基于BCMP排队网络的码头集卡预约优化模型

Optimization model for truck appointment based on BCMP queuing network

为减少外部集卡在集装箱码头的周转时间、提高码头作业效率,建立基于排队网络的集卡预约优化模型.该模型利用BCMP排队网络描述集卡在闸口和堆场的排队过程,在给定集卡到达调整量水平的限制下,优化每个时间段的预约份额.为求解模型,设计基于遗传算法和逐点固定流体近似算法(PSFFA)的求解方法,该方法用遗传算法搜索最优预约份额方案,基于PSFFA算法计算集卡在集装箱码头的周转时间.最后,利用算例对模型和算法的有效性进行了验证.结果表明,集卡预约优化模型可以有效地减少集卡在码头的周转时间,PSFFA方法可以准确地计算排队时间,较好地处理到达过程不平稳的排队问题.

An optimization model for truck appointment was developed to decrease the external truck turn time and to improve the terminal efficiency. In this model, a baskett Chandy Muntz Palacios （BCMP） queuing network was developed to describe the queuing process of trucks in the terminal, and the appointment quota of each period was optimized considering the constraints of adjustment quota. To solve the model, a method based on genetic algorithm （GA） and Point wise stationary fluid flow approximation （PSFFA） was designed. GA was used to search the optimal solution and PSFFA was designed to calculate the truck turn time. Finally, numerical experiments were provided to illustrate the validity of the model and the algorithm. Results indicate that proposed model can decrease the truck turn time efficiently, and the PSFFA algorithm can both estimate the queue waiting time accurately and tackle the no-stationary queue problem efficiently.