Application of case-based reasoning-Tabu search hybrid algorithm for rolling schedule optimization in tandem cold rolling

Abstract

Purpose The purpose of this study is to improve the global optimization ability of the Tabu search (TS) algorithm, and then improve the calculation efficiency and accuracy of rolling schedule in tandem cold rolling. Design/methodology/approach A case-based reasoning–Tabu search hybrid algorithm (CBRTS) has been presented. First, the case-based reasoning technology was adopted to obtain high-quality initial solution and then the TS algorithm was used for global optimization. Findings The optimization effect of CBRTS is compared with that of the traditional TS algorithm, and the analysis result indicates that the CBRTS has a faster convergence rate than TS, and the optimization results are closer to the global optimal. Meanwhile, the rolling schedule calculated by CBRTS is more reasonable, which can increase the production efficiency while giving full play to the capacity of equipment. Originality/value A CBRTS hybrid algorithm is presented. The strong dependence of the TS algorithm on the initial solution has been solved. The rolling schedule multi-objective optimization functions are established. The proposed algorithm is applied in a 1,450-mm tandem cold rolling production line. The improved method can reduce about half the iterations compared with the traditional one.