In a steel hot rolling mill, jobs are scheduled in groups for the production at two different production lines. The process of scheduling involves the selection and the sequencing of jobs as well as the assignment of selectable furnaces to some jobs. An optimal schedule minimizes unproductive times during the production while utilizing necessary retoolings of one production line as best as possible for the production at the other line. The resulting optimization problem is similar to a combination of several traveling salesman problems and orienteering problems.A method is presented to accurately model the alternating production process on both lines, including sequence-dependent setup times, production line retoolings, and the use of an induction furnace with three chambers. Based on this model, unproductive times occurring in a given schedule can be calculated. These times are minimized by a tailored optimization algorithm, which consists of a simulated annealing metaheuristic followed by a local search. The effective application and benefit of this algorithm are demonstrated in a case study.