Research on Production optimization of process workshop based on Wolf pack algorithm

In order to solve the scheduling optimization problem in the process-oriented food production and processing finished goods area, this paper proposes an improved wolf pack algorithm to solve the problem and obtain smaller completion time by optimizing the order loading sequence of the finished food production area. A backward learning strategy is used to construct a higher quality initial population, and the ability to jump out of local extremes is enhanced by adding a simulated annealing algorithm, which results in better overall convergence performance and higher stability of the algorithm. The effectiveness of the solution method is proved through simulation experiments, and the operation plan that can improve the production efficiency and meet the production scheduling requirements of process-oriented production enterprises is given under the premise of ensuring the production operation of enterprises.