{"title":"A Hierarchical Algorithm Model for the Scheduling Problem of Cold Chain Logistics Distribution Vehicles Based on Machine Vision","authors":"Yingsun Sun","doi":"10.1007/s44196-023-00347-x","DOIUrl":null,"url":null,"abstract":"Abstract With the continuous development of the market economy, the professional degree of the logistics industry is constantly improving, while the logistics distribution industry is also developing rapidly. The logistics distribution of the cold chain supply chain involves multiple distribution points, and the distance and time relationship between the distribution points are often not fully considered in the route planning, resulting in low distribution efficiency. The hierarchical algorithm model based on machine vision can solve the above problems to a certain extent. This paper takes two cold chain supply chain enterprises as the main research body, analyzes how to choose two kinds of COD and CCD sensors using machine vision, and the number of distribution vehicle scheduling. The simulation experiment was performed and at the end of the article it is summarized and discussed. According to the data sample, the two enterprises have the largest number of people satisfied with the supply chain logistics and distribution vehicle scheduling, but the number of people dissatisfied with enterprise A is 6 and 12% of the total. The number of people dissatisfied with enterprise B is 16 and 32% of the total number, It can be seen that although the number of people satisfied with the two enterprises is large, the number of people dissatisfied with enterprise B far exceeds that of enterprise A. At the same time, with the continuous research of supply chain logistics distribution vehicle scheduling, the research on machine vision is also facing new opportunities and challenges.","PeriodicalId":54967,"journal":{"name":"International Journal of Computational Intelligence Systems","volume":"225 1","pages":"0"},"PeriodicalIF":2.9000,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computational Intelligence Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s44196-023-00347-x","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract With the continuous development of the market economy, the professional degree of the logistics industry is constantly improving, while the logistics distribution industry is also developing rapidly. The logistics distribution of the cold chain supply chain involves multiple distribution points, and the distance and time relationship between the distribution points are often not fully considered in the route planning, resulting in low distribution efficiency. The hierarchical algorithm model based on machine vision can solve the above problems to a certain extent. This paper takes two cold chain supply chain enterprises as the main research body, analyzes how to choose two kinds of COD and CCD sensors using machine vision, and the number of distribution vehicle scheduling. The simulation experiment was performed and at the end of the article it is summarized and discussed. According to the data sample, the two enterprises have the largest number of people satisfied with the supply chain logistics and distribution vehicle scheduling, but the number of people dissatisfied with enterprise A is 6 and 12% of the total. The number of people dissatisfied with enterprise B is 16 and 32% of the total number, It can be seen that although the number of people satisfied with the two enterprises is large, the number of people dissatisfied with enterprise B far exceeds that of enterprise A. At the same time, with the continuous research of supply chain logistics distribution vehicle scheduling, the research on machine vision is also facing new opportunities and challenges.
期刊介绍:
The International Journal of Computational Intelligence Systems publishes original research on all aspects of applied computational intelligence, especially targeting papers demonstrating the use of techniques and methods originating from computational intelligence theory. The core theories of computational intelligence are fuzzy logic, neural networks, evolutionary computation and probabilistic reasoning. The journal publishes only articles related to the use of computational intelligence and broadly covers the following topics:
-Autonomous reasoning-
Bio-informatics-
Cloud computing-
Condition monitoring-
Data science-
Data mining-
Data visualization-
Decision support systems-
Fault diagnosis-
Intelligent information retrieval-
Human-machine interaction and interfaces-
Image processing-
Internet and networks-
Noise analysis-
Pattern recognition-
Prediction systems-
Power (nuclear) safety systems-
Process and system control-
Real-time systems-
Risk analysis and safety-related issues-
Robotics-
Signal and image processing-
IoT and smart environments-
Systems integration-
System control-
System modelling and optimization-
Telecommunications-
Time series prediction-
Warning systems-
Virtual reality-
Web intelligence-
Deep learning