Hybrid flow shop scheduling problem with flexible and complex assembly

With the development of industry, manufacturing systems become more and more complex. The traditional manufacturing industry is gradually changing to the intelligent manufacturing industry, which increases the difficulty of scheduling. In order to produce a final product, its parts need to be processed in a hybrid flow shop(HFS), and then assembled according to the predefined product bill of materials. The purpose of this study is to minimize the completion time of the last product. Aiming at the problem under consideration, a constraint programming (CP) model is established and solved by a commercial solver. Then, an iterative greedy algorithm (IGA) is proposed to solve this problem. In order to verify the performance of the algorithm, this paper compares it with simulated annealing (SA) and genetic algorithms (GA). Numerical results prove the effectiveness of the proposed model and solution method.