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Analyze the Effectiveness of the Algorithm for Agricultural Product Delivery Vehicle Routing Problem Based on Mathematical Model

Author

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  • Kairong Yu

    (Public Basic Course Department, Nanjing Institute of Industry and Technology, Nanjing, China)

  • Yang Liu

    (Jiangsu Agricultural Publicity, Education and Cultural Sports Center, Nanjing, China)

  • Ashutosh Sharma

    (Institute of Computer Technology and Information Security, Southern Federal University, Russia)

Abstract

With the recent development in the economic system, the requirement for logistic services has also increased gradually. This increased the demand for efficient and cost-effective delivery services without compromising the quality and timeliness. This has become a challenge to the logistic service providers to maintain the high-quality standards along with reliable delivery services. A mathematical equation model is proposed in this work to solve the problem of random quantity of agricultural products collected/distributed by working vehicle collection/distribution path planning. This article proposes a hybrid algorithm which combines the taboo algorithm search and the taboo hybrid algorithm to solve the problem. In the proposed algorithm, a large-scale problem is several small-scale problems to reduce the time complexity of the algorithm. Since randomness is much more complicated than certain types of problems, accurate algorithms can only be applied to a small range of problem types. The heuristic calculations involved in the development of algorithms make it a convenient simplified tool for the collection and distribution of random agricultural products. An average validation accuracy of 94% has been obtained for the proposed algorithm after completing 200 iterations while obtaining 94.37%, 94.57%, and 94.56% precision, recall, and F-score values, respectively.

Suggested Citation

  • Kairong Yu & Yang Liu & Ashutosh Sharma, 2021. "Analyze the Effectiveness of the Algorithm for Agricultural Product Delivery Vehicle Routing Problem Based on Mathematical Model," International Journal of Agricultural and Environmental Information Systems (IJAEIS), IGI Global, vol. 12(3), pages 26-38, July.
  • Handle: RePEc:igg:jaeis0:v:12:y:2021:i:3:p:26-38
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