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Heuristics for a Stochastic and Dynamic Routing Problem in Industrial Shipping

机译:工业航运中随机和动态路径问题的启发式

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摘要

Recent years have shown that static and deterministic vehicle routing problems can be solved to near optimality with acceptable computational times using metaheuristics. However, many real world applications are dynamic and include stochastic aspects, such as unknown future customer requests. Research has revealed that explicitly taking into account available stochastic information may yield benefits in these cases. Extending this research to industrial shipping, three different heuristics are considered and evaluated in terms of their ability to minimize transportation costs in this dynamic maritime planning problem.
机译:近年来的研究表明,使用元启发式算法可以在可接受的计算时间内将静态和确定性车辆路径问题解决到接近最佳状态。但是,许多现实世界的应用程序是动态的,并且包含随机方面,例如未知的未来客户请求。研究表明,在这些情况下,明确考虑可用的随机信息可能会带来好处。在将这项研究扩展到工业航运方面,考虑并评估了三种不同的启发式方法,以在此动态海事规划问题中最大程度地降低运输成本。

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