An Effective Heuristic for a Single-Machine Scheduling Problem with Family Setups and Resource Constraints

This paper presents a simple and effective iterated greedy heuristic to minimize the total tardiness in a single-machine scheduling problem. In this problem the jobs are classified in families and setup times are required between the processing of two jobs of different families. Each job requires a certain amount of resource that is supplied through upstream processes. The total resource consumed must not exceed the resource supply up. Therefore, jobs may have to wait and the machine has to be idle due to an insufficient availability of the resource. The iterated greedy heuristic is tested over an extensive computational experience on benchmark of instances from the literature and randomly generated in this work. Results show that the developed heuristic significantly outperforms a state-of-the-art heuristic in terms of solution quality.