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Ant Colony Algorithm Based Vehicle Routing Optimization of Tobacco Distribution

机译:基于蚁群算法的烟草分布的车辆路由优化

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Tobacco distribution Reducing energy consumption in tobacco logistics distribution process is one of the important measurements for energy saving and emission reduction of tobacco industry. Tobacco distribution vehicle routing optimization problem is essentially a typical NP problem. As a novel swarm intelligence optimization algorithm, Ant Colony Algorithm is adopted to solve the problem in the paper. First, a mathematical description of tobacco vehicle distribution problem is analyzed. And then, the basic principle of ACA is introduced followed by steps for tobacco logistics distribution vehicle routing using ACA. Finally, taking certain distribution network of Zhengzhou city for example, compared to simulated annealing algorithm, simulation experiments are carried out using an A CA procedure which is developed by matlab m-language to solve tobacco optimal distribution. The results show that it is feasible to solve Tobacco optimal distribution problem using ACA.
机译:减少烟草物流分配过程中能源消耗的烟草分布是烟草业节能减排的重要测量之一。烟草分配车辆路由优化问题基本上是一个典型的NP问题。作为一种新型群智能优化算法,采用蚁群算法来解决论文中的问题。首先,分析了烟草车辆分布问题的数学描述。然后,介绍了ACA的基本原理,然后介绍了使用ACA的烟草物流分配车辆路由的步骤。最后,考虑到郑州市的某些分销网络,与模拟退火算法相比,使用Matlab M-Language开发的CA程序进行仿真实验来解决烟草最佳分布。结果表明,使用ACA解决烟草最优分布问题是可行的。

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