Research on path optimization of reverse logistics network

Tao Fan; Ying Sun

doi:10.1117/12.2540994

27 November 2019 Research on path optimization of reverse logistics network

Tao Fan, Ying Sun

Proceedings Volume 11321, 2019 International Conference on Image and Video Processing, and Artificial Intelligence; 113211W (2019) https://doi.org/10.1117/12.2540994
Event: The Second International Conference on Image, Video Processing and Artifical Intelligence, 2019, Shanghai, China

Abstract

In the era of "Internet +", when using genetic algorithm to explore the recovery path optimization problem of reverse logistics network, it is found that the transportation time and vehicle arrangement have an important impact on the problem while requiring the shortest transportation path. In practical applications, when applying the Travelling Salesman Problem (TSP) method to solve the location and path planning problems of reverse logistics network, it is necessary to redesign the distance matrix of the method and the fitness of the solution algorithm. This paper designs a set of reverse logistics path planning model considering path, environmental impact and resource utilization.

Citation Download Citation

Tao Fan and Ying Sun "Research on path optimization of reverse logistics network", Proc. SPIE 11321, 2019 International Conference on Image and Video Processing, and Artificial Intelligence, 113211W (27 November 2019); https://doi.org/10.1117/12.2540994

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