Abstract
Due to the lack of systematically optimized logistics networks in many remote rural areas, the online sales of agricultural products in these areas have the disadvantages of high cost, high damage and slow speed. To address these logistic problems, this paper proposes a two-stage layout optimization model of agricultural product joint distribution centres based on the geographical features of remote rural areas. The number and location of distribution centres are selected in two stages to optimize the logistics network. Chengkou County, located in Chongqing city, China, has been selected as the study area. In the first stage, AP clustering is carried out using the distance between the logistics nodes of villages and towns, and the transit station of the source of agricultural products is obtained using the correlation between the nodes, which are regarded as alternative locations for the second-level logistics nodes. In the second stage, a joint distribution centre optimization model with the lowest cost is constructed. A fruit fly optimization algorithm is used to select the optimal locations from the alternative locations as the second-level logistics nodes and obtain the specific delivery path. Optimizing the logistics network of remote rural areas can reduce the logistics costs of agricultural products in these areas, promote online sales of agricultural products, and provide the government and logistics companies with theoretical references to open up new markets in remote areas.
Highlights
The logistics industry integrates transportation, warehousing, freight forwarding, information and other industries, thereby playing an important role in supporting the development of the national economy
Logistics cost of e-commerce for fresh agricultural products accounts for 25%-40% of the sales price, which is much higher than the logistics cost of other products, especially the distribution cost accounts for 35% of the total logistics cost [1]
Hiassat et al [29] considered the characteristics of perishable goods, established an optimization model of the distribution centre inventory problem, and used a genetic algorithm and local search heuristic method to solve it
Summary
T – fixed life of each agricultural product distribution centre; AS – average annual total supply in the region; θ –agricultural product corruption rate; p – average selling price of agricultural products; h – unit cost per delivery vehicle; hAB –unit cost per delivery vehicle from A to B; hBC –unit cost per delivery vehicle from B to C; xB –one Boolean variable to mark whether to build a distribution centre in B; 1,setting up a distribution center in candidate B xB = 0,otherwise yAB one Boolean variable to mark whether to transport agricultural products from A to B; 1, transport agricultural products from A to B yAB = 0, otherwise yBC one Boolean variable to mark whether to transport agricultural products from B to C; 1, transport agricultural products from B to C yBC = 0, otherwise
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