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A location-routing problem for cross-docking networks: A biogeography-based optimization algorithm

机译:跨码头网络的位置路由问题:一种基于生物地理的优化算法

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This paper considers a location-routing problem in a distribution network with a set of part suppliers, cross-docking centers and assembly plants known as customers. We develop a mixed integer nonlinear programming formulation for the problem in which the location for establishing the cross-docks is determined while simultaneously a fleet of vehicles are applied to transport goods from suppliers to the assembly plants via two transportation strategies: direct shipment and shipment through cross-dock (indirect shipment). In the second strategy, it is possible to have routes between suppliers. Not considering two problems of location and distribution planning simultaneously would result in increasing the costs of supplying parts since the transportation strategy has a huge effect on location of cross-docks. In the other words, if some loads can be directly shipped, then this kind of loads should not be taken into account in determining cross-docks location. Thus, a location- routing problem is presented for cross-docking system in this paper. The goal is to determine the location of cross-docks, allocating suppliers to them and routing decisions, so that the location cost and total shipping cost in the network are minimized, considering variable cost of servicing parts passed through cross-docks. The proposed model is NP-hard based on literature. Thus, a metaheuristic algorithm named Biogeography-based optimization (BBO) is utilized to solve the problem. In order to evaluate its efficiency, BBO results are compared with those of PSO, which is a well-known algorithm in the literature. Solving numerical examples for small size problem instances illustrates that the solving approach performs with a negligible gap relative to GAMS, while it performs much better than PSO in most cases in terms of total cost of the network and computational time.
机译:本文考虑了由一组零件供应商,跨码头中心和称为客户的装配厂组成的分销网络中的选址问题。我们针对以下问题开发了混合整数非线性规划公式:确定交叉码头的位置,同时通过两种运输策略将一队车辆应用于将货物从供应商运输到组装厂:直接装运和通过跨码头(间接装运)。在第二种策略中,可以在供应商之间建立路由。由于运输策略对交叉码头的位置影响很大,因此不能同时考虑位置和配送计划这两个问题会导致零件供应成本增加。换句话说,如果可以直接运输一些货物,则在确定跨码头位置时不应考虑此类货物。因此,本文提出了一种用于跨入库系统的位置路由问题。目标是确定跨码头的位置,为他们分配供应商并确定路线,从而考虑到穿过跨码头的零件维修成本,将位置成本和总运输成本降到最低。基于文献,提出的模型是NP难的。因此,一种名为基于生物地理的优化(BBO)的元启发式算法可用于解决该问题。为了评估其效率,将BBO结果与PSO的结果进行比较,PSO是文献中众所周知的算法。求解小型问题实例的数值示例说明,相对于GAMS,求解方法的性能可以忽略不计,而就网络的总成本和计算时间而言,它在大多数情况下比PSO更好。

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