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Logistics Terminal Distribution Mode and Path Optimization Based on Ant Colony Algorithm

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Abstract

In order to discuss the logistics distribution that directly affects the satisfaction of consumers for the entire online shopping activities, this article mainly studies the logistics terminal distribution mode and path optimization, and combined with the application of ant colony algorithm in the traveling salesman problem, analyses the basic principle and implementation process of ant colony algorithm. In addition, through reference to map and field research, we consider the route length and road conditions (slope and congestion) of the the regional distribution point, and collect and draw the geographic information surrounding area A. Moreover, some key parameters in ant colony algorithm in value are chosen, and with the collected information as a concrete example, MATLAB simulation is carried out for the logistics terminal distribution path optimization based on ant colony algorithm, and its scientific nature and feasibility are verified. The simulation results showed that the ant colony algorithm has good feasibility so that it can be widely applied. As a result, it is concluded that the application of ant colony algorithm has great significance in the exploration of the logistics terminal distribution path optimization.

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Acknowledgements

The authors acknowledge “Basic Tasks of Technical forecasting” commissioned by CASTED, College Scientific Research Project of China University of Political Science and Law (Grant No. 17ZFG63001), Training and Supporting Project for Young or Middle-aged Teachers of China University of Political Science and Law, and NSF of China (Grant No. L1422009).

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Correspondence to Xu Pang.

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Yu, M., Yue, G., Lu, Z. et al. Logistics Terminal Distribution Mode and Path Optimization Based on Ant Colony Algorithm. Wireless Pers Commun 102, 2969–2985 (2018). https://doi.org/10.1007/s11277-018-5319-z

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  • DOI: https://doi.org/10.1007/s11277-018-5319-z

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