Analyze the Effectiveness of the Algorithm for Agricultural Product Delivery Vehicle Routing Problem Based on Mathematical Model
Kairong Yu,
Yang Liu and
Ashutosh Sharma
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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
International Journal of Agricultural and Environmental Information Systems (IJAEIS), 2021, vol. 12, issue 3, 26-38
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.
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jaeis0:v:12:y:2021:i:3:p:26-38
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