Multi-objective reentrant scheduling problem for semiconductor workshop

In semiconductor manufacturing workshop，the machine states are often inconsistent when the products re-enter the machine． The traditional reentrant scheduling methods are unsuitable for semiconductor workshop scheduling because of the characteristic of inconsistent．According to the characteristics of semiconductor workshop，the multi-objective reentrant hybrid flow shop scheduling problem for the semiconductor manufacturing workshop was proposed．A mathematical model of this problem was built based on minimizing the maximum completion time，reducing product failure rate and decreasing machine process switching times．An optimal foraging algorithm based on substantial uncertainty factor (SUF_OFA) was proposed．In proposed algorithm，the grey correlation analyzing and the Pythagorean fuzzy set of MYCIN uncertainty factor were used to build the multi-objective processing strategy．The substantial uncertainty factors of Pareto solutions were adopted as the fitness value of the optimal foraging algorithm．The workpiece number was used as the coding scheme，and the feasible scheduling solution was decoded by the three-stage decoding method．Through different experiments and a semiconductor workshop case，the proposed algorithm was compared with four other algorithms．The proposed model was verified and the performance of the proposed algorithm was analyzed．The results show that SUF_OFA has significant advantages in solving the multi-objective reentrant hybrid flow shop scheduling problem. © 2023 Huazhong University of Science and Technology. All rights reserved.