An adaptive intelligent method for manufacturing process optimization in steelworks

In this paper, the manufacturing process in iron and steel manufacturing systems is modeled as the m-machine no-wait flowshop scheduling problem with sequence-dependent setup times. To avoid extreme uneven utilization of machine capacity, makespan is considered as the minimization criterion. An adaptive intelligent method named GEIM is proposed, which is a new meta-heuristic on the basis of greedy randomized adaptive search procedure and evolutionary local search, for the considered problem. Path-relinking strategy is adopted to bridge the local optimum and elite solutions for exploring the solution spaces. Attributes of elite solutions are extracted to guide the local search process and an adaptive control mechanism is provided for the diversification of elite set at the end phase of the searching process. The proposed algorithm is compared with some existing approaches from the literature on classical benchmark instances. Computational results show that the proposed algorithm outperforms the existing ones and is suitable for optimizing the manufacturing process in steelworks.