This data article describes 30 instances of the real-world problem of sequencing steel coils in a continuous galvanizing line. Each instance is represented by a cost matrix that gives information of the cost of sequencing each pair of coils or items together (e.g. a transition). Some transitions are forbidden due to technical limitations of the line and/or because of the properties of the coils, what makes the problem more challenging. These costs were previously obtained by a cost model that estimates the final cost of each transition for a set of coils to be sequenced in the line. Although the instances come from this real context, the problem can be theoretically seen as finding a minimum cost Hamiltonian path (e.g. a minimum cost feasible production sequence with all the coils appearing just once). It is a well-known NP-Hard combinatorial optimization problem. Since these instances represent real challenges found in the industry, they can be very useful for algorithm development and testing. Due to the cost distributions obtained for the given coils, just finding a feasible sequence can be a challenging task, especially for some types of approximate algorithms (Alvarez-Gil et al., 2022).
Keywords: Combinatorial optimization; Manufacturing scheduling; Metaheuristics; Steel industry.
© 2022 The Authors. Published by Elsevier Inc.