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基于混合鲸鱼算法的生鲜农产品产地型冷库选址与路径优化研究

Research on origin-based cold storage location and routing optimization of fresh agricultural products based on hybrid whale algorithm.

作者信息

Zhou Xueyan, Li Jin, Xie Fengjie, Fang Jing

机构信息

Xi'an University of Posts & Telecommunications, Xian, Shaanxi, China.

Xi'an Yifen Intelligent Technology Co., Ltd, Xian, Shaanxi, China.

出版信息

Sci Rep. 2024 Sep 10;14(1):21078. doi: 10.1038/s41598-024-72170-z.

Abstract

With the focus on the insufficient origin-based cold storage in China, this study investigates the location and routing problem (LRP) of origin-based cold storage for fresh agricultural products. This study considers the loss of fresh agricultural products in different environments during transportation and presents a cold storage LRP model. To address this issue, a hybrid whale algorithm with heuristic rules is designed, and the effectiveness of the algorithm is verified by standard instances. Finally, taking Chenggu County as a practical case, the influence of cold storage capacity and farmers' demand for refrigeration are analysed. Experimental results show that the proposed algorithm has a good effect in solving medium-scale LRP. As the storage capacity increases, the total cost of the system can be increased by 0.086%. As farmers' demand for refrigeration increases, the total cost of the system can be increased by 34.034%. Farmers' demand has a greater impact on the system's total costs than the cold storage capacity. When optimizing the cold storage layout, changes in fresh agricultural product output in the next few years can be roughly predicted, and the most economical optimization scheme can be obtained.

摘要

针对我国产地型冷库不足的问题,本研究对新鲜农产品产地型冷库的选址与路径问题(LRP)进行了研究。本研究考虑了新鲜农产品在运输过程中在不同环境下的损耗情况,并提出了一种冷库LRP模型。为解决该问题,设计了一种带有启发式规则的混合鲸鱼算法,并通过标准实例验证了该算法的有效性。最后,以城固县为例,分析了冷库容量和农户冷藏需求的影响。实验结果表明,所提算法在解决中等规模LRP问题时具有良好效果。随着存储容量的增加,系统总成本可增加0.086%。随着农户冷藏需求的增加,系统总成本可增加34.034%。农户需求对系统总成本的影响大于冷库容量。在优化冷库布局时,可以大致预测未来几年新鲜农产品产量的变化,并获得最经济的优化方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5092/11387780/6e298b43ca94/41598_2024_72170_Fig1_HTML.jpg

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