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Optimization of Location-Routing Problem in Emergency Logistics Considering Carbon Emissions

机译:考虑碳排放的应急物流中选址问题的优化

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摘要

In order to solve the optimization problem of emergency logistics system, this paper provides an environmental protection point of view and combines with the overall optimization idea of emergency logistics system, where a fuzzy low-carbon open location-routing problem (FLCOLRP) model in emergency logistics is constructed with the multi-objective function, which includes the minimum delivery time, total costs and carbon emissions. Taking into account the uncertainty of the needs of the disaster area, this article illustrates a triangular fuzzy function to gain fuzzy requirements. This model is tackled by a hybrid two-stage algorithm: Particle swarm optimization is adopted to obtain the initial optimal solution, which is further optimized by tabu search, due to its global optimization capability. The effectiveness of the proposed algorithm is verified by the classic database in LRP. What’s more, an example of a post-earthquake rescue is used in the model for acquiring reliable conclusions, and the application of the model is tested by setting different target weight values. According to these results, some constructive proposals are propounded for the government to manage emergency logistics and for the public to aware and measure environmental emergency after disasters.
机译:为了解决应急物流系统的优化问题,本文提出了一种环保的观点,并结合了应急物流系统的整体优化思想,提出了应急物流系统的模糊低碳开放式选址路由问题(FLCOLRP)模型。物流具有多目标功能,包括最短的交货时间,总成本和碳排放量。考虑到灾区需求的不确定性,本文说明了获得模糊需求的三角模糊函数。该模型通过混合两阶段算法解决:采用粒子群算法获得初始最优解,由于其全局优化能力,可以通过禁忌搜索对其进行进一步优化。 LRP中的经典数据库验证了该算法的有效性。此外,该模型还使用了地震后救援的示例来获得可靠的结论,并通过设置不同的目标体重值来测试该模型的应用。根据这些结果,提出了一些建设性的建议,以帮助政府管理紧急物流,并让公众了解和衡量灾难后的环境紧急情况。

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