Research on the optimized route of cold chain logistics transportation of fresh products in context of energy-saving and emission reduction

Liu, Zheng; Guo, Hangxin; Zhao, Yuanjun; Hu, Bin; Shi, Lihua; Lang, Lingling; Huang, Bangtong

doi:10.3934/mbe.2021100

Cited by 30 publications

(13 citation statements)

References 8 publications

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“…is representation can both visually represent user interests and initially cluster users according to thematic interest categories to facilitate subsequent community discovery [34][35][36][37]. Figure 2 presents the segmentation tree vector space model.…”

Section: User Interest Representationmentioning

confidence: 99%

Clustering Merchants and Accurate Marketing of Products Using the Segmentation Tree Vector Space Model

Ding

2022

Mathematical Problems in Engineering

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Using social commerce users as the data source, a reasonable and effective interest expression mechanism is used to construct an interest graph of sample users to achieve the purpose of clustering merchants and users as well as realizing accurate marketing of products. By introducing an improved vector space model, the segmentation tree vector space model, to express the interests of the target user group and, on this basis, using the complex network analysis tool Gephi to construct an interest graph, based on the user interest graph, we use Python to implement the K-means algorithm and the users of the sample set according to interest topics for community discovery. The experimental results show that the interests of the sample users are carefully divided, each user is divided into different thematic communities according to different interests, and the constructed interest graph is more satisfactory. The research design of the social commerce user interest mapping scheme is highly feasible, reasonable, and effective and provides new ideas for the research of interest graph, and the boundaries of thematic communities based on interests are clear.

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Section: User Interest Representationmentioning

confidence: 99%

Clustering Merchants and Accurate Marketing of Products Using the Segmentation Tree Vector Space Model

Ding

2022

Mathematical Problems in Engineering

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“…Zhao et al [ 10 ] established an inventory control simulation model for a mixed supply chain of process industries represented by metallurgy, petrochemicals, and pharmaceuticals. In addition, many scholars extended intelligent algorithms to the inventory strategy problem, and Liu et al [ 11 ] studied the inventory and path optimization problem of fresh cold chain in the context of energy-saving and emission reduction with the help of genetic algorithm and hybrid algorithm. Shaikh et al [ 12 ] studied a fuzzy inventory model with allowable delayed payments considering inventory backlog and out-of-stock problem with the help of particle swarm algorithm.…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Pharmaceutical Reagent Inventory Strategy Based on Contract Shelf Life and Patient Demand

Liu

Qian

Zhao

et al. 2022

Contrast Media & Molecular Imaging

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As the function and R&D level of in vitro diagnostic reagents continue to improve, the need for hospitals for in vitro diagnostic reagents in clinical diagnosis also keeps increasing. However, under the influence of management, process, technology, equipment, materials, employees, and other unexpected disturbing factors, the output of reagents often has random uncertainty, and it is difficult to provide the finished products required by orders on time, in quality and quantity. A secondary supply chain consisting of reagent manufacturers, distributors, and hospitals is constructed, and the inventory control models of in vitro diagnostic reagent supply chain under three strategies of centralized decision-making, hospital-owned inventory, and reagent distributor-managed inventory are established, respectively, and the maximum expected returns of the supply chain system under different strategies are analyzed to achieve the optimal production decision of reagent manufacturers and the optimal procurement decision of hospitals. The results show that reducing the random output probability and patient demand uncertainty has a significant effect on improving the expected return of in vitro diagnostic reagent supply chain, and as the random output probability of reagent manufacturers and patient consumption demand uncertainty increase, the strategy of managing inventory by distributors in collaboration is always better than the strategy of managing inventory by hospitals' own warehouses, which can achieve higher expected return and better inventory quantity, but when the out-of-stock cost of hospitals is too high above a certain threshold, the hospital will tend to adopt the self-inventory strategy.

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“…Fresh products refer to the primary products sold without deep processing such as cooking and production, which are only kept fresh and simply sorted on the shelves, as well as the commodities of on-site processing categories such as bread and cooked food. Fresh products are mainly circulated through the cold chain, but the high cost of cold chain logistics and easy disconnection in transportation will lead to the increase of carbon emissions [1]. e overall demand is large.…”

Section: Introductionmentioning

confidence: 99%

Promotion Strategy of Low-Carbon Consumption of Fresh Food Based on Willingness Behavior

Zhao

Zhong

Zhu

2022

Mathematical Problems in Engineering

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The research on the influencing factors of residents’ low-carbon consumption willingness and low-carbon consumption behavior of fresh food has certain practical guiding significance. Existing studies have analyzed the low-carbon consumption willingness, but the factors considered are not comprehensive and the degree of fit needs to be improved. Therefore, this paper starts with 37 variables from six aspects: demographic factors, psychological factors, low-carbon related knowledge, external factors, policy norms, and product factors. The binary logistic model is used to carry out regression analysis on low-carbon consumption willingness and low-carbon consumption behavior, and the fitting degree is higher and reaches about 90%. The regression results show that sense of responsibility, government tax, low-carbon product quality, and low-carbon product price have a significant impact on residents’ low-carbon consumption willingness. Whether there are fake and shoddy products in the market and whether the products are really of low carbon have a significant impact on low-carbon consumption behavior. Finally, starting from the three subjects of government, enterprises, and residents, this paper puts forward targeted suggestions to improve residents’ low-carbon consumption willingness and promote residents’ low-carbon consumption behavior, in order to promote low-carbon consumption.

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Research on the optimized route of cold chain logistics transportation of fresh products in context of energy-saving and emission reduction

Cited by 30 publications

References 8 publications

Clustering Merchants and Accurate Marketing of Products Using the Segmentation Tree Vector Space Model

Clustering Merchants and Accurate Marketing of Products Using the Segmentation Tree Vector Space Model

[Retracted] Pharmaceutical Reagent Inventory Strategy Based on Contract Shelf Life and Patient Demand

Promotion Strategy of Low-Carbon Consumption of Fresh Food Based on Willingness Behavior

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