Abstract
The flexible job shop scheduling problem (FJSP) is a generalization of the classical job shop scheduling problem (JSP), where each operation is allowed to be processed by any machine from a given set, rather than one specified machine. In this paper, two algorithm modules, namely, hybrid harmony search (HHS) and large neighborhood search (LNS) are developed for the FJSP with makespan criterion. The HHS is an evolutionary-based algorithm with the memetic paradigm, while the LNS is typical of constraint-based approaches. To form a stronger search mechanism, an integrated search method is proposed for the FJSP based on the two algorithms, which starts with the HHS, and then the solution is further improved by the LNS. Computational simulations and comparisons demonstrate that, the proposed HHS alone can effectively solve some medium to large FJSP instances, when integrated with the LNS, it shows competitive performance with state-of-the-art algorithms on very hard and large-scale problems, some new upper bounds among the unsolved benchmark instances have even been found.