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首页> 外文期刊>Journal of Intelligent Manufacturing >A hybrid meta-heuristic algorithm for vehicle routing and packing problem with cross-docking
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A hybrid meta-heuristic algorithm for vehicle routing and packing problem with cross-docking

机译:交叉扩展的车辆路由和包装问题的混合元启发式算法

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摘要

Cross-docking is a relatively new logistics strategy that has a great potential to eliminate storage cost and speed up the product flows. This paper considers the vehicle routing and packing problem with cross-docking and presents a mixed integer linear mathematical model. In the model, a set of trucks are used to transport products from suppliers to customers through cross-docking centers. Each supplier and customer node can be visited only once and directly shipping is not allowed from suppliers to customers. Moreover, truck capacities are identified with physical dimensional limits on the contrary of weight or amount of load. The objective of the study is to determine the vehicle routes that minimize the total distance. Due to the complexity of the mathematical model, a hybrid meta-heuristic algorithm (HMA), which integrates tabu search (TS) algorithm within simulated annealing (SA) algorithm, is proposed to solve the problem. Proposed HMA is tested on a well-known benchmark problem data set and compared with the SA and TS solutions. Results show that proposed HMA can produce effective solutions and outperforms the SA and TS especially for the large-sized problems.
机译:交叉扩展是一种相对较新的物流策略,具有消除储存成本并加快产品流量的巨大潜力。本文考虑了交叉扩展的车辆路由和包装问题,并呈现混合整数线性数学模型。在该模型中,一套卡车用于通过交叉扩展中心将产品从供应商运送到客户。每个供应商和客户节点只能访问一次,不允许从客户提供直接发货。此外,卡车容量与物理尺寸限制识别,相反的重量或负载量。该研究的目的是确定最小化总距离的车辆路线。由于数学模型的复杂性,提出了一种混合元 - 启发式算法(HMA),它在模拟退火(SA)算法内集成了禁忌搜索(TS)算法,以解决问题。提出的HMA在众所周知的基准测试数据集上进行测试,并与SA和TS解决方案进行比较。结果表明,建议的HMA可以产生有效的解决方案,优于SA和TS,特别是对于大型问题。

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