Research On Flexible Job Shop Scheduling Method Based On Sparrow Search Algorith

With the continuous improvement of the level of China’s manufacturing industry,the production mode shows the discretization characteristics of multi variety and small batch.In order to improve production efficiency,the processing and manufacturing workshop must fully utilize production resources and reasonably arrange production plans.The quality of workshop scheduling technology is the key to whether production plans can be reasonably arranged.The Flexible Job Shop Scheduling Problem is one of the most representative scheduling problems in workshop scheduling,characterized by multiple constraints between machines and processes,which is more in line with the current production situation and has important research significance.On the basis of summarizing and analyzing the current research status at home and abroad,this article establishes a mathematical model of single objective FJSP and solves it by improving the Sparrow Search Algorithm(SSA).Firstly,in order to enable the algorithm to handle discrete scheduling problems,this paper designs an encoding conversion method suitable for FJSP two-stage encoding,achieving the conversion between the continuous solution space of the algorithm and the discrete scheduling solution.Secondly,this article designs an initialization strategy that combines population randomization with combinatorial heuristic rules to improve the quality of the initial population and the convergence speed of the algorithm.Once again,this article introduces the variable neighborhood search algorithm to act on the optimal individual among the discoverers,in order to deeply tap into their potential,improve the quality of the discoverers,and thus enhance the depth of the search.This strategy utilizes critical path information to guide the search process,further enhancing the efficiency and accuracy of the algorithm.Finally,in order to overcome possible local optimal solution problems and maintain population diversity.This article designs an adaptive Cauchy Gaussian mutation strategy to further improve the accuracy and robustness of the algorithm.In order to verify the effectiveness of the algorithm,this paper uses a standard test case to carry out simulation experiments.The improved discrete sparrow search algorithm proposed in this article demonstrates excellent efficiency and accuracy in solving FJSP.At the same time,the effectiveness of the algorithm improvement strategy has also been confirmed.Then,the improved algorithm was used to solve two workshop scheduling instances and compared with other algorithms.For complex workshop scheduling problems,the algorithm proposed in this article can provide an efficient solution.