Iterated local search for distributed multiple assembly no-wait flowshop scheduling

Driven by the pressing needs in coordinating and synchronizing multi-plant facilities for efficient production and manufacturing, distributed assembly permutation flowshop scheduling problem (DAPFSP) has been becoming the focus of concern of evolutionary computing and operations research, which is a typical NP-hard combinatorial optimization problem. In this paper, we propose a novel generalized version of DAPFSP, where multiple assembly factories exist rather than only one assembly factory in the conventional DAPFSP, meanwhile no-wait constraint exists in the processing stage. We name this new model as the distributed multiple assembly permutation flowshop scheduling problem with no-wait, abbreviated as DMAPFSP-NW. We propose hybrid iterated local search with simulated annealing (ILS-SA) for the proposed scheduling model. Simulation results based on 27 large-scale benchmark problems show that our proposed ILS-SA can effectively solve the DMAPFSP-NW.