Hybrid flow shop scheduling with assembly operations and key objectives: A novel neighborhood search

Abstract

In this study hybrid flow shop scheduling problem (HFSP) with unrelated parallel machines and assembly operations is considered, in which two tardiness objectives are minimized as key ones under the bounded condition that makespan is not allowed to exceed an upper bound. A novel neighborhood search with memory and global exchange (NSMG) is then proposed based on a part-based representation and a new dominance called limited dominance. Global exchange is cooperated with neighborhood search to improve solution quality. Extensive experiments are conducted to test the performance of NSMG finally. The results show that the preferential handling strategy of key objectives is reasonable and effective and NSMG is a very competitive method for the considered HFSP.