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首页> 外文会议>IEEE International Conference on Automation Science and Engineering >Multi-point to multi-point multi-task fourth party logistics routing problem considering tardiness risk
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Multi-point to multi-point multi-task fourth party logistics routing problem considering tardiness risk

机译：考虑延误风险的多点到多点多任务的第四方物流路径问题

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摘要

Under uncertainty environment, tardiness risk is inevitable when we transport logistics task. In this paper, aimed at the problem of multi-point to multi-point and multi-task, we propose path optimization mathematical model considering tardiness risk which is described by Value-at-Risk. The model aims to minimize tardiness risk's maximum of all tasks based on the constraints of total cost, carrying capacity requirements; we can measure tardiness risk of different confidence levels. Considering to the characteristics of the problem, we design the Ant Colony Optimization (ACO) algorithm and the Dynamic Ant Colony Optimization (DACO) algorithm. According to numerical analysis, we can conclude that the DACO algorithm can improve the stability of solution and global search ability compared with the ACO algorithm, and tardiness risk increases with the increase of the confidence level.
机译：在不确定的环境下，运输物流任务时拖延风险是不可避免的。本文针对多点到多点，多任务的问题，提出了一种考虑时延风险的路径优化数学模型，该模型由风险价值描述。该模型旨在根据总成本，承载能力要求的约束，将所有任务的拖延风险的最大值降至最低。我们可以衡量不同置信度下的拖延风险。针对问题的特点，设计了蚁群优化算法和动态蚁群优化算法。通过数值分析，可以得出结论：与ACO算法相比，DACO算法可以提高解的稳定性和全局搜索能力，且拖后风险随着置信度的提高而增加。

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