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The Research on Low Carbon Logistics Routing Optimization Based on DNA-Ant Colony Algorithm

机译:基于DNA-蚁群算法的低碳物流路径优化研究

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摘要

As the energy conservation and emission reduction and sustainable development have become the hot topics in the world, low carbon issues catch more and more attention. Logistics, which is one of the important economic activities, plays a crucial role in the low carbon development. Logistics leads to some significant issues about consuming energy and carbon emissions. Therefore, reducing energy consumption and carbon emissions has become the inevitable trend for logistics industry. Low carbon logistics is introduced in these situations. In this paper, from the microcosmic aspects, we will bring the low carbon idea in the path optimization issues and change the amount of carbon emissions into carbon emissions cost to establish the path optimization model based on the optimization objectives of the lowest cost of carbon emissions. According to different levels of air pollution, we will establish the double objectives path optimization model with the consideration of carbon emissions cost and economy cost. Use DNA-ant colony algorithm to optimize and simulate the model. The simulation indicates that DNA-ant colony algorithm could find a more reasonable solution for low carbon logistics path optimization problems.
机译:随着节能减排和可持续发展成为世界上的热门话题,低碳问题越来越受到关注。物流是重要的经济活动之一,在低碳发展中起着至关重要的作用。物流导致一些有关消耗能源和碳排放的重大问题。因此,降低能耗和碳排放已成为物流业的必然趋势。在这些情况下引入了低碳物流。本文从微观的角度出发,将低碳理念引入路径优化问题,将碳排放量转化为碳排放成本,以最低碳排放成本的优化目标为基础,建立路径优化模型。 。根据空气污染水平的不同,我们将在考虑碳排放成本和经济成本的基础上建立双目标路径优化模型。使用DNA-蚁群算法优化和仿真模型。仿真表明,DNA-蚁群算法可以为低碳物流路径优化问题找到更合理的解决方案。

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