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Dynamic-inventory Ship Routing Problem (D-ISRP) Model Considering Port Dwelling time Information

机译:考虑港口停留时间信息的动态库存船舶选路问题(D-ISRP)模型

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Longer dwelling time in a port cause cost inefficiency and uncertainty in ship scheduling. Due to higher port charge, unnecessary queue in a port should be avoided since it will reduce ship utilization and increase operation cost. In the context of industrial shipping, the lateness of a trip of a ship may also cause inventory stock out in the destination ports. These risks will be disadvantages for the supplier since he is also responsible to manage the inventory of commodity in the depot of buyers. The supplier will be charged penalty cost for the lateness under the agreement of Vendor Managed Inventory (VMI). The model which combines transportation and inventory decisions in literature is called Inventory Routing Problem (IRP). In this research, we modify the basic model of IRP for ship scheduling to include some decisions dynamically made to response the information of dwelling time received during the journey: speed of ships and rerouting. We called the proposed model Dynamic-Inventory Ship Routing Problem (D-ISRP). We develop a mixed-integer non-linear program (MINLP) to solve this problem. The objective is to minimize the total cost while avoiding the inventory stock out. The total cost consists of sail bunker consumption cost, port bunker consumption cost, ship operational cost, port charge, loading/unloading cost, and penalty cost for late delivery. Since the proposed model is an NP-hard problem thus a heuristic model is preferred. Specifically, we design a new efficient heuristic algorithm based on the model of interaction theory. The algorithm determines the ship schedule based on the interaction coefficient of ships and ports. The matrices of interaction coefficient of ships and ports is determined by considering the ability of ships to supply port's demand and vice versa. In order to examine the behavior of the model, we conduct some numerical experiments. Our experiments concluded that the proposed algorithm has a high reliability to solve the D-ISRP problem in efficient computational time. We also conduct some experiments to compare between the decisions of speed reduction and rerouting in anticipating updated dwelling time information.
机译:在港口停留时间较长会导致成本低效和船舶调度的不确定性。由于较高的港口收费,应避免港口不必要的排队,因为这会降低船舶利用率并增加运营成本。在工业运输的情况下,船舶出行的延迟也可能导致目的地港口的库存积压。对于供应商来说,这些风险将是不利的,因为他还负责管理买方仓库中的商品库存。根据供应商管理的库存(VMI)的协议,将向供应商收取滞纳金。在文献中结合运输和库存决策的模型称为库存路由问题(IRP)。在这项研究中,我们修改了用于船舶调度的IRP基本模型,以包括动态做出的一些决策,以响应在旅途中收到的停留时间信息:船舶的速度和路线变更。我们将提出的模型称为“动态库存船舶路由问题”(D-ISRP)。我们开发了一个混合整数非线性程序(MINLP)来解决此问题。目的是最大程度地降低总成本,同时避免库存不足。总成本包括风帆燃料消耗成本,港口燃料消耗成本,船舶运营成本,港口费用,装卸成本以及后期交付的罚款成本。由于所提出的模型是NP难题,因此启发式模型是首选。具体而言,我们基于交互理论模型设计了一种新的高效启发式算法。该算法根据船舶和港口的相互作用系数确定船舶计划。船舶与港口相互作用系数的矩阵是通过考虑船舶满足港口需求的能力来确定的,反之亦然。为了检查模型的行为,我们进行了一些数值实验。我们的实验得出结论,该算法在高效计算时间内解决D-ISRP问题具有很高的可靠性。我们还进行了一些实验,以比较减速和重新路由的决定,以预测更新的居住时间信息。

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