Paper
14 February 2024 Used electric vehicle batteries recycling network based on multi-objective iterative local optimization algorithm
Jing Zhang, Hengyi Ru, Bowen Shi, Hengqing Guo
Author Affiliations +
Proceedings Volume 13018, International Conference on Smart Transportation and City Engineering (STCE 2023); 130183P (2024) https://doi.org/10.1117/12.3024016
Event: International Conference on Smart Transportation and City Engineering (STCE 2023), 2023, Chongqing, China
Abstract
The industrialization of electric vehicles has brought with it a large number of used batteries. In order to support the development of electric vehicles, it is necessary to recycle waste batteries in an efficient way. This paper investigates the path planning problem in the recycling process of used batteries for electric vehicles. The recycling path is required to be optimized to minimize the total cost. In contrast to existing research, a multi-level recycling network for used batteries in electric vehicles is designed taking into account practical scenarios, while the balance of vehicle working distances is introduced into the objective function. In the model construction, the workflow of the recycling network is designed in a distributed manner and the variance weighting of the vehicle working distance is introduced into the objective function. The study combines iterative local search algorithm with variable neighborhood search algorithm to design a multi-objective iterative local optimization algorithm. The improved model is proven with the algorithm to solve practical problems and can be used for future research.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Jing Zhang, Hengyi Ru, Bowen Shi, and Hengqing Guo "Used electric vehicle batteries recycling network based on multi-objective iterative local optimization algorithm", Proc. SPIE 13018, International Conference on Smart Transportation and City Engineering (STCE 2023), 130183P (14 February 2024); https://doi.org/10.1117/12.3024016
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KEYWORDS
Batteries

Mathematical optimization

Process modeling

Network architectures

Radon

Genetic algorithms

Industry

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