Optimization of food sampling inspection based on discrete sparrow search algorithm

Abstract

ObjectiveTo propose an efficient optimized method for food sampling inspection based on discrete sparrow search algorithm.MethodsBy coding the sampling points, calculating and optimizing the paths between different codes, a discrete sparrow search algorithm was constructed, compared and verified with other known algorithms.ResultsThe discrete sparrow search algorithm constructed in this research could obtain the known optimal solution for Burma14, Bays29, Oliver30 and Att48, etc. For examples such as Kioa100 and Ch130, the deviation rates obtained by this algorithm were 0.1% and 1%, respectively, which were better than traditional genetic algorithms (the deviation rates were 3% and 4.2%, respectively).ConclusionThe food sampling path optimization method based on the discrete sparrow search algorithm created in this research had better performance in terms of solution accuracy and convergence speed, which was helpful to the actual work of double random sampling point generation and sampling path optimization. It provided feasible algorithmic support for the random inspection information system.

Keywords

• food sampling inspection
• double random
• path optimization
• travelling salesman problem
• discrete sparrow search algorithm