Location optimization of fresh food e-commerce front warehouse

被引:0
|
作者
Zhang, Dezheng [1 ]
Chen, Shuai [1 ]
Zhou, Na [1 ]
Shi, Pu [1 ]
机构
[1] Hebei Univ Engn, Sch Management Engn & Business, Handan 056038, Peoples R China
关键词
front warehouse; location-allocation; immune algorithm; genetic algorithm;
D O I
10.3934/mbe.2023667
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
The ongoing emergence of COVID-19 and the maturation of cold chain technology, have aided in the rapid development of the fresh produce e-commerce industry. Taking into account the characteristics of consumers' demand for fresh products, this paper constructs a location allocation model of a front warehouse for fresh e-commerce with the objective of minimizing the total cost. An improved immune optimization algorithm is proposed in this paper, and the effectiveness of the proposed algorithm is demonstrated by a real case study. The results show that the improved immune optimization algorithm outperforms the traditional genetic algorithm in terms of solution accuracy; the proposed location model can effectively help fresh produce e-commerce enterprises open new frontend warehouses when demand is increasing, as well as provide optimal economic decision-making for front warehouse layout.
引用
收藏
页码:14899 / 14919
页数:21
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