A two-stage assignment strategy for the robust scheduling of dual-resource constrained stochastic job shop scheduling problems

This paper addresses the job shop scheduling problems with stochastic processing times (SJSSP) under machine-worker dual-resource constraints. Considering the difference in worker's proficiency level, a robust scheduling approach is adopted. And then the machine-worker dual-resource constrained robust scheduling model of SJSSP based on the expected scenario of processing times (DR-SJSSP-EPS) is formulated. In view of the requirements of DR-SJSSP-ESP for the rational assignment of the workers, we propose a two-stage assignment strategy (TSAS), which can decrease the random disturbance of the processing times as well as its impact on the scheduling performance. Furthermore, a multi-objective hybrid estimation of distribution algorithm (MO-HEDA) is employed to solve the DR-SJSSP-ESP. At last, the effectiveness of the proposed method to solve the DR-SJSSP-ESP in the job shop manufacturing system is verified according to the simulation results. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.