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- W4383959600 abstract "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 front-end warehouses when demand is increasing, as well as provide optimal economic decision-making for front warehouse layout." @default.
- W4383959600 created "2023-07-12" @default.
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- W4383959600 date "2023-01-01" @default.
- W4383959600 modified "2023-10-16" @default.
- W4383959600 title "Location optimization of fresh food e-commerce front warehouse" @default.
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- W4383959600 doi "https://doi.org/10.3934/mbe.2023667" @default.
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