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Tramp ship routing and scheduling with voyage separation requirements

机译:有航程分离要求的流浪者船的路线和调度

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In this paper we explore tramp ship routing and scheduling. Tramp ships operate much like taxies following the available demand. Tramp operators can determine some of their demand in advance by entering into long-term contracts and then try to maximise profits from optional voyages found in the spot market. Routing and scheduling a tramp fleet to best utilise fleet capacity according to current demand is therefore an ongoing and complicated problem. Here we add further complexity to the routing and scheduling problem by incorporating voyage separation requirements that enforce a minimum time spread between some voyages. The incorporation of these separation requirements helps balance the conflicting objectives of maximising profit for the tramp operator and minimising inventory costs for the charterer, since these costs increase if similar voyages are not performed with some separation in time. We have developed a new and exact branch-and-price procedure for this problem. We use a dynamic programming algorithm to generate columns and describe a time window branching scheme used to enforce the voyage separation requirements which we relax in the master problem. Computational results show that our algorithm in general finds optimal solutions very quickly and performs much faster compared to an earlier a priori path generation method. Finally, we compare our method to an earlier adaptive large neighbourhood search heuristic and find that on similar-sized instances our approach generally uses less time to find the optimal solution than the adaptive large neighbourhood search method uses to find a heuristic solution.
机译:在本文中,我们探索流浪船的航行路线和调度。根据可用需求,流浪者船只的运作方式与出租车一样。流浪者运营商可以通过签订长期合同来预先确定他们的一些需求,然后尝试从现货市场中发现的可选航程中获取最大利润。因此,根据当前需求来安排和调度流浪者车队以最佳利用车队的能力是一个持续而复杂的问题。在这里,我们通过合并在某些航程之间执行最短时间间隔的航程分隔要求,进一步增加了路由和调度问题的复杂性。这些分离要求的合并有助于平衡以下冲突目标:使流浪者获得最大利润,并使租船人的库存成本最小化,因为如果不按时进行类似的航行,这些成本就会增加。我们针对此问题开发了一种新的精确分价程序。我们使用动态编程算法来生成列,并描述用于执行航程分离要求的时间窗口分支方案,我们在主要问题中对此有所放松。计算结果表明,与较早的先验路径生成方法相比,我们的算法通常可以非常快速地找到最优解,并且执行速度要快得多。最后,我们将我们的方法与早期的自适应大邻域搜索启发式方法进行比较,发现在类似大小的实例上,与自适应大邻域搜索方法来查找启发式方法相比,我们的方法通常花费更少的时间来找到最优解。

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