Production Scheduling Optimization of An Aviation Bearing Manufacturing Enterprise Based on Teaching-Learning-based Optimization

Abstract

This article is based on an aviation bearing manufacturing and wind power bearing manufacturing enterprise production scheduling for its key process optimization, in Qingdao, Shandong. The production scheduling is aimed at the shortest delivery time, and the production scheduling assessment indicator is the on-time delivery rate of orders. This article, based on the production process and production mode characteristics of the enterprise, improves the convergence ability of the Teaching-learning-based optimization (TLBO) in the early stage and the detail search ability in the later stage by optimizing the static teaching factor function and algorithm retrieval method of the classic algorithm. By combining Levy flight to further enhance the algorithm's global search ability and reduce the probability of falling into local optima. The theoretical reliability of the algorithm was verified by comparing the calculation result of the MK calculation example with other algorithms. The reliability of the algorithm in actual production was verified through the long-term order execution data and order delivery rate of the enterprise.