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Robust optimisation model for the cold food chain logistics problem under uncertainty

机译:不确定性条件下冷食链物流问题的鲁棒优化模型

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摘要

In the last two decades, food safety has become one of the main concerns in the area of logistics and supply chain management and also in cold chain. Safety is a critically sensitive area in this category as if the required safety conditions are not satisfied during the logistics process, foods will soon deteriorate and probably become unsafe to use by customers. Thus, the problem of cold food safety has encouraged serious attentions among the logistics practitioners. However, because of the complexity in nature of such problems, research so far is limited to the quantitative models with deterministic parameters and the robustness of this nature still remains unanswered. In this paper, a robust optimisation model has been developed aiming to maximise the food safety aspects and thus to minimise the logistics cost of the cold chain system under various uncertainties and customers time windows restrictions. The model has been solved by artificial bee colony intelligence algorithm through MATLAB 8 software. Finally, the results are analysed for possible real world considerations in order to propose some key practical highlights.
机译:在过去的二十年中,食品安全已成为物流和供应链管理以及冷链领域的主要关注之一。安全是此类别中的关键敏感区域,因为在物流过程中无法满足所需的安全条件,食品将很快变质,并且可能变得对客户不安全。因此,冷食品安全问题引起了物流从业者的高度重视。但是,由于此类问题本质上的复杂性,到目前为止,研究仅限于具有确定性参数的定量模型,而这种性质的鲁棒性仍未得到解答。在本文中,已经开发了一个鲁棒的优化模型,旨在最大化食品安全性,从而在各种不确定性和客户时间窗口限制下将冷链系统的物流成本降至最低。该模型已通过MATLAB 8软件通过人工蜂群智能算法进行求解。最后,对结果进行分析,以考虑可能的现实世界,以提出一些关键的实用亮点。

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